GNSS Signal Tracking Performance Improvement for Highly Dynamic Receivers by Gyroscopic Mounting Crystal Oscillator.

PubMed

Abedi, Maryam; Jin, Tian; Sun, Kewen

2015-08-31

In this paper, the efficiency of the gyroscopic mounting method is studied for a highly dynamic GNSS receiver's reference oscillator for reducing signal loss. Analyses are performed separately in two phases, atmospheric and upper atmospheric flights. Results show that the proposed mounting reduces signal loss, especially in parts of the trajectory where its probability is the highest. This reduction effect appears especially for crystal oscillators with a low elevation angle g-sensitivity vector. The gyroscopic mounting influences frequency deviation or jitter caused by dynamic loads on replica carrier and affects the frequency locked loop (FLL) as the dominant tracking loop in highly dynamic GNSS receivers. In terms of steady-state load, the proposed mounting mostly reduces the frequency deviation below the one-sigma threshold of FLL (1σ(FLL)). The mounting method can also reduce the frequency jitter caused by sinusoidal vibrations and reduces the probability of signal loss in parts of the trajectory where the other error sources accompany this vibration load. In the case of random vibration, which is the main disturbance source of FLL, gyroscopic mounting is even able to suppress the disturbances greater than the three-sigma threshold of FLL (3σ(FLL)). In this way, signal tracking performance can be improved by the gyroscopic mounting method for highly dynamic GNSS receivers.

Social costs enforce honesty of a dynamic signal of motivation.

PubMed

Ligon, Russell A; McGraw, Kevin J

2016-10-26

Understanding the processes that promote signal reliability may provide important insights into the evolution of diverse signalling strategies among species. The signals that animals use to communicate must comprise mechanisms that prohibit or punish dishonesty, and social costs of dishonesty have been demonstrated for several fixed morphological signals (e.g. colour badges of birds and wasps). The costs maintaining the honesty of dynamic signals, which are more flexible and potentially cheatable, are unknown. Using an experimental manipulation of the dynamic visual signals used by male veiled chameleons (Chamaeleo calyptratus) during aggressive interactions, we tested the idea that the honesty of rapid colour change signals is maintained by social costs. Our results reveal that social costs are an important mechanism maintaining the honesty of these dynamic colour signals-'dishonest' chameleons whose experimentally manipulated coloration was incongruent with their contest behaviour received more physical aggression than 'honest' individuals. This is the first demonstration, to the best our knowledge, that the honesty of a dynamic signal of motivation-physiological colour change-can be maintained by the social costliness of dishonesty. Behavioural responses of signal receivers, irrespective of any specific detection mechanisms, therefore prevent chameleon cheaters from prospering. © 2016 The Author(s).

Dynamic Vibrotactile Signals for Forward Collision Avoidance Warning Systems

PubMed Central

Meng, Fanxing; Gray, Rob; Ho, Cristy; Ahtamad, Mujthaba

2015-01-01

Objective: Four experiments were conducted in order to assess the effectiveness of dynamic vibrotactile collision-warning signals in potentially enhancing safe driving. Background: Auditory neuroscience research has demonstrated that auditory signals that move toward a person are more salient than those that move away. If this looming effect were found to extend to the tactile modality, then it could be utilized in the context of in-car warning signal design. Method: The effectiveness of various vibrotactile warning signals was assessed using a simulated car-following task. The vibrotactile warning signals consisted of dynamic toward-/away-from-torso cues (Experiment 1), dynamic versus static vibrotactile cues (Experiment 2), looming-intensity- and constant-intensity-toward-torso cues (Experiment 3), and static cues presented on the hands or on the waist, having either a low or high vibration intensity (Experiment 4). Results: Braking reaction times (BRTs) were significantly faster for toward-torso as compared to away-from-torso cues (Experiments 1 and 2) and static cues (Experiment 2). This difference could not have been attributed to differential responses to signals delivered to different body parts (i.e., the waist vs. hands; Experiment 4). Embedding a looming-intensity signal into the toward-torso signal did not result in any additional BRT benefits (Experiment 3). Conclusion: Dynamic vibrotactile cues that feel as though they are approaching the torso can be used to communicate information concerning external events, resulting in a significantly faster reaction time to potential collisions. Application: Dynamic vibrotactile warning signals that move toward the body offer great potential for the design of future in-car collision-warning system. PMID:25850161

Social costs enforce honesty of a dynamic signal of motivation

PubMed Central

McGraw, Kevin J.

2016-01-01

Understanding the processes that promote signal reliability may provide important insights into the evolution of diverse signalling strategies among species. The signals that animals use to communicate must comprise mechanisms that prohibit or punish dishonesty, and social costs of dishonesty have been demonstrated for several fixed morphological signals (e.g. colour badges of birds and wasps). The costs maintaining the honesty of dynamic signals, which are more flexible and potentially cheatable, are unknown. Using an experimental manipulation of the dynamic visual signals used by male veiled chameleons (Chamaeleo calyptratus) during aggressive interactions, we tested the idea that the honesty of rapid colour change signals is maintained by social costs. Our results reveal that social costs are an important mechanism maintaining the honesty of these dynamic colour signals—‘dishonest’ chameleons whose experimentally manipulated coloration was incongruent with their contest behaviour received more physical aggression than ‘honest’ individuals. This is the first demonstration, to the best our knowledge, that the honesty of a dynamic signal of motivation—physiological colour change—can be maintained by the social costliness of dishonesty. Behavioural responses of signal receivers, irrespective of any specific detection mechanisms, therefore prevent chameleon cheaters from prospering. PMID:27798310

Inelastic and Dynamic Fracture and Stress Analyses

NASA Technical Reports Server (NTRS)

Atluri, S. N.

1984-01-01

Large deformation inelastic stress analysis and inelastic and dynamic crack propagation research work is summarized. The salient topics of interest in engine structure analysis that are discussed herein include: (1) a path-independent integral (T) in inelastic fracture mechanics, (2) analysis of dynamic crack propagation, (3) generalization of constitutive relations of inelasticity for finite deformations , (4) complementary energy approaches in inelastic analyses, and (5) objectivity of time integration schemes in inelastic stress analysis.

Dynamics of Mechanical Signal Transmission through Prestressed Stress Fibers

PubMed Central

Hwang, Yongyun; Barakat, Abdul I.

2012-01-01

Transmission of mechanical stimuli through the actin cytoskeleton has been proposed as a mechanism for rapid long-distance mechanotransduction in cells; however, a quantitative understanding of the dynamics of this transmission and the physical factors governing it remains lacking. Two key features of the actin cytoskeleton are its viscoelastic nature and the presence of prestress due to actomyosin motor activity. We develop a model of mechanical signal transmission through prestressed viscoelastic actin stress fibers that directly connect the cell surface to the nucleus. The analysis considers both temporally stationary and oscillatory mechanical signals and accounts for cytosolic drag on the stress fibers. To elucidate the physical parameters that govern mechanical signal transmission, we initially focus on the highly simplified case of a single stress fiber. The results demonstrate that the dynamics of mechanical signal transmission depend on whether the applied force leads to transverse or axial motion of the stress fiber. For transverse motion, mechanical signal transmission is dominated by prestress while fiber elasticity has a negligible effect. Conversely, signal transmission for axial motion is mediated uniquely by elasticity due to the absence of a prestress restoring force. Mechanical signal transmission is significantly delayed by stress fiber material viscosity, while cytosolic damping becomes important only for longer stress fibers. Only transverse motion yields the rapid and long-distance mechanical signal transmission dynamics observed experimentally. For simple networks of stress fibers, mechanical signals are transmitted rapidly to the nucleus when the fibers are oriented largely orthogonal to the applied force, whereas the presence of fibers parallel to the applied force slows down mechanical signal transmission significantly. The present results suggest that cytoskeletal prestress mediates rapid mechanical signal transmission and allows

Detection of chaotic dynamics in human gait signals from mobile devices

NASA Astrophysics Data System (ADS)

DelMarco, Stephen; Deng, Yunbin

2017-05-01

The ubiquity of mobile devices offers the opportunity to exploit device-generated signal data for biometric identification, health monitoring, and activity recognition. In particular, mobile devices contain an Inertial Measurement Unit (IMU) that produces acceleration and rotational rate information from the IMU accelerometers and gyros. These signals reflect motion properties of the human carrier. It is well-known that the complexity of bio-dynamical systems gives rise to chaotic dynamics. Knowledge of chaotic properties of these systems has shown utility, for example, in detecting abnormal medical conditions and neurological disorders. Chaotic dynamics has been found, in the lab, in bio-dynamical systems data such as electrocardiogram (heart), electroencephalogram (brain), and gait data. In this paper, we investigate the following question: can we detect chaotic dynamics in human gait as measured by IMU acceleration and gyro data from mobile phones? To detect chaotic dynamics, we perform recurrence analysis on real gyro and accelerometer signal data obtained from mobile devices. We apply the delay coordinate embedding approach from Takens' theorem to reconstruct the phase space trajectory of the multi-dimensional gait dynamical system. We use mutual information properties of the signal to estimate the appropriate delay value, and the false nearest neighbor approach to determine the phase space embedding dimension. We use a correlation dimension-based approach together with estimation of the largest Lyapunov exponent to make the chaotic dynamics detection decision. We investigate the ability to detect chaotic dynamics for the different one-dimensional IMU signals, across human subject and walking modes, and as a function of different phone locations on the human carrier.

Entropy for the Complexity of Physiological Signal Dynamics.

PubMed

Zhang, Xiaohua Douglas

2017-01-01

Recently, the rapid development of large data storage technologies, mobile network technology, and portable medical devices makes it possible to measure, record, store, and track analysis of biological dynamics. Portable noninvasive medical devices are crucial to capture individual characteristics of biological dynamics. The wearable noninvasive medical devices and the analysis/management of related digital medical data will revolutionize the management and treatment of diseases, subsequently resulting in the establishment of a new healthcare system. One of the key features that can be extracted from the data obtained by wearable noninvasive medical device is the complexity of physiological signals, which can be represented by entropy of biological dynamics contained in the physiological signals measured by these continuous monitoring medical devices. Thus, in this chapter I present the major concepts of entropy that are commonly used to measure the complexity of biological dynamics. The concepts include Shannon entropy, Kolmogorov entropy, Renyi entropy, approximate entropy, sample entropy, and multiscale entropy. I also demonstrate an example of using entropy for the complexity of glucose dynamics.

Cell cycle dynamics in a response/signalling feedback system with a gap.

PubMed

Gong, Xue; Buckalew, Richard; Young, Todd; Boczko, Erik

2014-01-01

We consider a dynamical model of cell cycles of n cells in a culture in which cells in one specific phase (S for signalling) of the cell cycle produce chemical agents that influence the growth/cell cycle progression of cells in another phase (R for responsive). In the case that the feedback is negative, it is known that subpopulations of cells tend to become clustered in the cell cycle; while for a positive feedback, all the cells tend to become synchronized. In this paper, we suppose that there is a gap between the two phases. The gap can be thought of as modelling the physical reality of a time delay in the production and action of the signalling agents. We completely analyse the dynamics of this system when the cells are arranged into two cell cycle clusters. We also consider the stability of certain important periodic solutions in which clusters of cells have a cyclic arrangement and there are just enough clusters to allow interactions between them. We find that the inclusion of a small gap does not greatly alter the global dynamics of the system; there are still large open sets of parameters for which clustered solutions are stable. Thus, we add to the evidence that clustering can be a robust phenomenon in biological systems. However, the gap does effect the system by enhancing the stability of the stable clustered solutions. We explain this phenomenon in terms of contraction rates (Floquet exponents) in various invariant subspaces of the system. We conclude that in systems for which these models are reasonable, a delay in signalling is advantageous to the emergence of clustering.

Microwave signal processing with photorefractive dynamic holography

NASA Astrophysics Data System (ADS)

Fotheringham, Edeline B.

Have you ever found yourself listening to the music playing from the closest stereo rather than to the bromidic (uninspiring) person speaking to you? Your ears receive information from two sources but your brain listens to only one. What if your cell phone could distinguish among signals sharing the same bandwidth too? There would be no "full" channels to stop you from placing or receiving a call. This thesis presents a nonlinear optical circuit capable of distinguishing uncorrelated signals that have overlapping temporal bandwidths. This so called autotuning filter is the size of a U.S. quarter dollar and requires less than 3 mW of optical power to operate. It is basically an oscillator in which the losses are compensated with dynamic holographic gain. The combination of two photorefractive crystals in the resonator governs the filter's winner-take-all dynamics through signal-competition for gain. This physical circuit extracts what is mathematically referred to as the largest principal component of its spatio-temporal input space. The circuit's practicality is demonstrated by its incorporation in an RF-photonic system. An unknown mixture of unknown microwave signals, received by an antenna array, constitutes the input to the system. The output electronically returns one of the original microwave signals. The front-end of the system down converts the 10 GHz microwave signals and amplifies them before the signals phase modulate optical beams. The optical carrier is suppressed from these beams so that it may not be considered as a signal itself to the autotuning filter. The suppression is achieved with two-beam coupling in a single photorefractive crystal. The filter extracts the more intense of the signals present on the carrier-suppressed input beams. The detection of the extracted signal restores the microwave signal to an electronic form. The system, without the receiving antenna array, is packaged in a 13 x 18 x 6″ briefcase. Its power consumption equals that

Dynamic force signal processing system of a robot manipulator

NASA Technical Reports Server (NTRS)

Uchiyama, M.; Kitagaki, K.; Hakomori, K.

1987-01-01

If dynamic noises such as those caused by the inertia forces of the hand can be eliminated from the signal of the force sensor installed on the wrist of the robot manipulator and if the necessary information of the external force can be detected with high sensitivity and high accuracy, a fine force feedback control for robots used in high speed and various fields will be possible. As the dynamic force sensing system, an external force estimate method with the extended Kalman filter is suggested and simulations and tests for a one axis force were performed. Later a dynamic signal processing system of six axes was composed and tested. The results are presented.

Enzyme Sequestration as a Tuning Point in Controlling Response Dynamics of Signalling Networks

PubMed Central

Ollivier, Julien F.; Soyer, Orkun S.

2016-01-01

Signalling networks result from combinatorial interactions among many enzymes and scaffolding proteins. These complex systems generate response dynamics that are often essential for correct decision-making in cells. Uncovering biochemical design principles that underpin such response dynamics is a prerequisite to understand evolved signalling networks and to design synthetic ones. Here, we use in silico evolution to explore the possible biochemical design space for signalling networks displaying ultrasensitive and adaptive response dynamics. By running evolutionary simulations mimicking different biochemical scenarios, we find that enzyme sequestration emerges as a key mechanism for enabling such dynamics. Inspired by these findings, and to test the role of sequestration, we design a generic, minimalist model of a signalling cycle, featuring two enzymes and a single scaffolding protein. We show that this simple system is capable of displaying both ultrasensitive and adaptive response dynamics. Furthermore, we find that tuning the concentration or kinetics of the sequestering protein can shift system dynamics between these two response types. These empirical results suggest that enzyme sequestration through scaffolding proteins is exploited by evolution to generate diverse response dynamics in signalling networks and could provide an engineering point in synthetic biology applications. PMID:27163612

HYPNOTIC TACTILE ANESTHESIA: Psychophysical and Signal-Detection Analyses

PubMed Central

Tataryn, Douglas J.; Kihlstrom, John F.

2017-01-01

Two experiments that studied the effects of hypnotic suggestions on tactile sensitivity are reported. Experiment 1 found that suggestions for anesthesia, as measured by both traditional psychophysical methods and signal detection procedures, were linearly related to hypnotizability. Experiment 2 employed the same methodologies in an application of the real-simulator paradigm to examine the effects of suggestions for both anesthesia and hyperesthesia. Significant effects of hypnotic suggestion on both sensitivity and bias were found in the anesthesia condition but not for the hyperesthesia condition. A new bias parameter, C′, indicated that much of the bias found in the initial analyses was artifactual, a function of changes in sensitivity across conditions. There were no behavioral differences between reals and simulators in any of the conditions, though analyses of postexperimental interviews suggested the 2 groups had very different phenomenal experiences. PMID:28230465

Calcium dynamics and signaling in vascular regulation: computational models

PubMed Central

Tsoukias, Nikolaos Michael

2013-01-01

Calcium is a universal signaling molecule with a central role in a number of vascular functions including in the regulation of tone and blood flow. Experimentation has provided insights into signaling pathways that lead to or affected by Ca2+ mobilization in the vasculature. Mathematical modeling offers a systematic approach to the analysis of these mechanisms and can serve as a tool for data interpretation and for guiding new experimental studies. Comprehensive models of calcium dynamics are well advanced for some systems such as the heart. This review summarizes the progress that has been made in modeling Ca2+ dynamics and signaling in vascular cells. Model simulations show how Ca2+ signaling emerges as a result of complex, nonlinear interactions that cannot be properly analyzed using only a reductionist's approach. A strategy of integrative modeling in the vasculature is outlined that will allow linking macroscale pathophysiological responses to the underlying cellular mechanisms. PMID:21061306

Imaging of dynamic ion signaling during root gravitropism.

PubMed

Monshausen, Gabriele B

2015-01-01

Gravitropic signaling is a complex process that requires the coordinated action of multiple cell types and tissues. Ca(2+) and pH signaling are key components of gravitropic signaling cascades and can serve as useful markers to dissect the molecular machinery mediating plant gravitropism. To monitor dynamic ion signaling, imaging approaches combining fluorescent ion sensors and confocal fluorescence microscopy are employed, which allow the visualization of pH and Ca(2+) changes at the level of entire tissues, while also providing high spatiotemporal resolution. Here, I describe procedures to prepare Arabidopsis seedlings for live cell imaging and to convert a microscope for vertical stage fluorescence microscopy. With this imaging system, ion signaling can be monitored during all phases of the root gravitropic response.

Dynamic behaviour of a rolling tyre: Experimental and numerical analyses

NASA Astrophysics Data System (ADS)

Gonzalez Diaz, Cristobal; Kindt, Peter; Middelberg, Jason; Vercammen, Stijn; Thiry, Christophe; Close, Roland; Leyssens, Jan

2016-03-01

Based on the results of experimental and numerical analyses, the effect of rotation on the tyre dynamic behaviour is investigated. Better understanding of these effects will further improve the ability to control and optimize the noise and vibrations that result from the interaction between the road surface and the rolling tyre. Therefore, more understanding in the complex tyre dynamic properties will contribute to develop tyre design strategies to lower the tyre/road noise while less affecting other tyre performances. The presented work is performed in the framework of the European industry-academia project TIRE-DYN, with partners Goodyear, Katholieke Universiteit Leuven and LMS International. The effect of rotation on the tyre dynamic behaviour is quantified for different operating conditions of the tyre, such as load, air pressure and rotation speed. By means of experimental and numerical analyses, the effects of rotation on the tyre dynamic behaviour are studied.

Dynamic Regulation of Tgf-B Signaling by Tif1γ: A Computational Approach

PubMed Central

Andrieux, Geoffroy; Fattet, Laurent; Le Borgne, Michel; Rimokh, Ruth; Théret, Nathalie

2012-01-01

TIF1γ (Transcriptional Intermediary Factor 1 γ) has been implicated in Smad-dependent signaling by Transforming Growth Factor beta (TGF-β). Paradoxically, TIF1γ functions both as a transcriptional repressor or as an alternative transcription factor that promotes TGF-β signaling. Using ordinary differential-equation models, we have investigated the effect of TIF1γ on the dynamics of TGF-β signaling. An integrative model that includes the formation of transient TIF1γ-Smad2-Smad4 ternary complexes is the only one that can account for TGF-β signaling compatible with the different observations reported for TIF1γ. In addition, our model predicts that varying TIF1γ/Smad4 ratios play a critical role in the modulation of the transcriptional signal induced by TGF-β, especially for short stimulation times that mediate higher threshold responses. Chromatin immunoprecipitation analyses and quantification of the expression of TGF-β target genes as a function TIF1γ/Smad4 ratios fully validate this hypothesis. Our integrative model, which successfully unifies the seemingly opposite roles of TIF1γ, also reveals how changing TIF1γ/Smad4 ratios affect the cellular response to stimulation by TGF-β, accounting for a highly graded determination of cell fate. PMID:22461896

Dynamic facial expressions of emotion transmit an evolving hierarchy of signals over time.

PubMed

Jack, Rachael E; Garrod, Oliver G B; Schyns, Philippe G

2014-01-20

Designed by biological and social evolutionary pressures, facial expressions of emotion comprise specific facial movements to support a near-optimal system of signaling and decoding. Although highly dynamical, little is known about the form and function of facial expression temporal dynamics. Do facial expressions transmit diagnostic signals simultaneously to optimize categorization of the six classic emotions, or sequentially to support a more complex communication system of successive categorizations over time? Our data support the latter. Using a combination of perceptual expectation modeling, information theory, and Bayesian classifiers, we show that dynamic facial expressions of emotion transmit an evolving hierarchy of "biologically basic to socially specific" information over time. Early in the signaling dynamics, facial expressions systematically transmit few, biologically rooted face signals supporting the categorization of fewer elementary categories (e.g., approach/avoidance). Later transmissions comprise more complex signals that support categorization of a larger number of socially specific categories (i.e., the six classic emotions). Here, we show that dynamic facial expressions of emotion provide a sophisticated signaling system, questioning the widely accepted notion that emotion communication is comprised of six basic (i.e., psychologically irreducible) categories, and instead suggesting four. Copyright © 2014 Elsevier Ltd. All rights reserved.

Possible signals of vacuum dynamics in the Universe

NASA Astrophysics Data System (ADS)

Peracaula, Joan Solà; de Cruz Pérez, Javier; Gómez-Valent, Adrià

2018-05-01

We study a generic class of time-evolving vacuum models which can provide a better phenomenological account of the overall cosmological observations as compared to the ΛCDM. Among these models, the running vacuum model (RVM) appears to be the most motivated and favored one, at a confidence level of ˜3σ. We further support these results by computing the Akaike and Bayesian information criteria. Our analysis also shows that we can extract fair signals of dynamical dark energy (DDE) by confronting the same set of data to the generic XCDM and CPL parametrizations. In all cases we confirm that the combined triad of modern observations on Baryonic Acoustic Oscillations, Large Scale Structure formation, and the Cosmic Microwave Background, provide the bulk of the signal sustaining a possible vacuum dynamics. In the absence of any of these three crucial data sources, the DDE signal can not be perceived at a significant confidence level. Its possible existence could be a cure for some of the tensions existing in the ΛCDM when confronted to observations.

All-optical signal processing using dynamic Brillouin gratings

PubMed Central

Santagiustina, Marco; Chin, Sanghoon; Primerov, Nicolay; Ursini, Leonora; Thévenaz, Luc

2013-01-01

The manipulation of dynamic Brillouin gratings in optical fibers is demonstrated to be an extremely flexible technique to achieve, with a single experimental setup, several all-optical signal processing functions. In particular, all-optical time differentiation, time integration and true time reversal are theoretically predicted, and then numerically and experimentally demonstrated. The technique can be exploited to process both photonic and ultra-wide band microwave signals, so enabling many applications in photonics and in radio science. PMID:23549159

Dynamic tracking down-conversion signal processing method based on reference signal for grating heterodyne interferometer

NASA Astrophysics Data System (ADS)

Wang, Guochao; Yan, Shuhua; Zhou, Weihong; Gu, Chenhui

2012-08-01

Traditional displacement measurement systems by grating, which purely make use of fringe intensity to implement fringe count and subdivision, have rigid demands for signal quality and measurement condition, so they are not easy to realize measurement with nanometer precision. Displacement measurement with the dual-wavelength and single-grating design takes advantage of the single grating diffraction theory and the heterodyne interference theory, solving quite well the contradiction between large range and high precision in grating displacement measurement. To obtain nanometer resolution and nanometer precision, high-power subdivision of interference fringes must be realized accurately. A dynamic tracking down-conversion signal processing method based on the reference signal is proposed. Accordingly, a digital phase measurement module to realize high-power subdivision on field programmable gate array (FPGA) was designed, as well as a dynamic tracking down-conversion module using phase-locked loop (PLL). Experiments validated that a carrier signal after down-conversion can constantly maintain close to 100 kHz, and the phase-measurement resolution and phase precision are more than 0.05 and 0.2 deg, respectively. The displacement resolution and the displacement precision, corresponding to the phase results, are 0.139 and 0.556 nm, respectively.

Dynamic multiprotein assemblies shape the spatial structure of cell signaling.

PubMed

Nussinov, Ruth; Jang, Hyunbum

2014-01-01

Cell signaling underlies critical cellular decisions. Coordination, efficiency as well as fail-safe mechanisms are key elements. How the cell ensures that these hallmarks are at play are important questions. Cell signaling is often viewed as taking place through discrete and cross-talking pathways; oftentimes these are modularized to emphasize distinct functions. While simple, convenient and clear, such models largely neglect the spatial structure of cell signaling; they also convey inter-modular (or inter-protein) spatial separation that may not exist. Here our thesis is that cell signaling is shaped by a network of multiprotein assemblies. While pre-organized, the assemblies and network are loose and dynamic. They contain transiently-associated multiprotein complexes which are often mediated by scaffolding proteins. They are also typically anchored in the membrane, and their continuum may span the cell. IQGAP1 scaffolding protein which binds proteins including Raf, calmodulin, Mek, Erk, actin, and tens more, with actin shaping B-cell (and likely other) membrane-anchored nanoclusters and allosterically polymerizing in dynamic cytoskeleton formation, and Raf anchoring in the membrane along with Ras, provides a striking example. The multivalent network of dynamic proteins and lipids, with specific interactions forming and breaking, can be viewed as endowing gel-like properties. Collectively, this reasons that efficient, productive and reliable cell signaling takes place primarily through transient, preorganized and cooperative protein-protein interactions spanning the cell rather than stochastic, diffusion-controlled processes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Analysing the Effect of Demand Uncertainty in Dynamic Pricing with EAs

NASA Astrophysics Data System (ADS)

Shakya, Siddhartha; Oliveira, Fernando; Owusu, Gilbert

Dynamic pricing is a pricing strategy where a firm adjust the price for their products and services as a function of its perceived demand at different times. In this paper, we show how Evolutionary algorithms (EA) can be used to analyse the effect of demand uncertainty in dynamic pricing. The experiments are conducted in a range of dynamic pricing problems considering a number of different stochastic scenarios with a number of different EAs. The results are analysed, which suggest that higher demand fluctuation may not have adverse effect to the profit in comparison to the lower demand fluctuation, and that the reliability of EA for finding accurate policy could be higher when there is higher fluctuation then when there is lower fluctuation.

Comparisons of several aerodynamic methods for application to dynamic loads analyses

NASA Technical Reports Server (NTRS)

Kroll, R. I.; Miller, R. D.

1976-01-01

The results of a study are presented in which the applicability at subsonic speeds of several aerodynamic methods for predicting dynamic gust loads on aircraft, including active control systems, was examined and compared. These aerodynamic methods varied from steady state to an advanced unsteady aerodynamic formulation. Brief descriptions of the structural and aerodynamic representations and of the motion and load equations are presented. Comparisons of numerical results achieved using the various aerodynamic methods are shown in detail. From these results, aerodynamic representations for dynamic gust analyses are identified. It was concluded that several aerodynamic methods are satisfactory for dynamic gust analyses of configurations having either controls fixed or active control systems that primarily affect the low frequency rigid body aircraft response.

Predicting Essential Components of Signal Transduction Networks: A Dynamic Model of Guard Cell Abscisic Acid Signaling

PubMed Central

Li, Song; Assmann, Sarah M; Albert, Réka

2006-01-01

Plants both lose water and take in carbon dioxide through microscopic stomatal pores, each of which is regulated by a surrounding pair of guard cells. During drought, the plant hormone abscisic acid (ABA) inhibits stomatal opening and promotes stomatal closure, thereby promoting water conservation. Dozens of cellular components have been identified to function in ABA regulation of guard cell volume and thus of stomatal aperture, but a dynamic description is still not available for this complex process. Here we synthesize experimental results into a consistent guard cell signal transduction network for ABA-induced stomatal closure, and develop a dynamic model of this process. Our model captures the regulation of more than 40 identified network components, and accords well with previous experimental results at both the pathway and whole-cell physiological level. By simulating gene disruptions and pharmacological interventions we find that the network is robust against a significant fraction of possible perturbations. Our analysis reveals the novel predictions that the disruption of membrane depolarizability, anion efflux, actin cytoskeleton reorganization, cytosolic pH increase, the phosphatidic acid pathway, or K+ efflux through slowly activating K+ channels at the plasma membrane lead to the strongest reduction in ABA responsiveness. Initial experimental analysis assessing ABA-induced stomatal closure in the presence of cytosolic pH clamp imposed by the weak acid butyrate is consistent with model prediction. Simulations of stomatal response as derived from our model provide an efficient tool for the identification of candidate manipulations that have the best chance of conferring increased drought stress tolerance and for the prioritization of future wet bench analyses. Our method can be readily applied to other biological signaling networks to identify key regulatory components in systems where quantitative information is limited. PMID:16968132

Stability analysis of dynamic collaboration model with control signals on two lanes

NASA Astrophysics Data System (ADS)

Li, Zhipeng; Zhang, Run; Xu, Shangzhi; Qian, Yeqing; Xu, Juan

2014-12-01

In this paper, the influence of control signals on the stability of two-lane traffic flow is mainly studied by applying control theory with lane changing behaviors. We present the two-lane dynamic collaboration model with lateral friction and the expressions of feedback control signals. What is more, utilizing the delayed feedback control theory to the two-lane dynamic collaboration model with control signals, we investigate the stability of traffic flow theoretically and the stability conditions for both lanes are derived with finding that the forward and lateral feedback signals can improve the stability of traffic flow while the backward feedback signals cannot achieve it. Besides, direct simulations are conducted to verify the results of theoretical analysis, which shows that the feedback signals have a significant effect on the running state of two vehicle groups, and the results are same with the theoretical analysis.

Gating based on internal/external signals with dynamic correlation updates.

PubMed

Wu, Huanmei; Zhao, Qingya; Berbeco, Ross I; Nishioka, Seiko; Shirato, Hiroki; Jiang, Steve B

2008-12-21

Precise localization of mobile tumor positions in real time is critical to the success of gated radiotherapy. Tumor positions are usually derived from either internal or external surrogates. Fluoroscopic gating based on internal surrogates, such as implanted fiducial markers, is accurate however requiring a large amount of imaging dose. Gating based on external surrogates, such as patient abdominal surface motion, is non-invasive however less accurate due to the uncertainty in the correlation between tumor location and external surrogates. To address these complications, we propose to investigate an approach based on hybrid gating with dynamic internal/external correlation updates. In this approach, the external signal is acquired at high frequency (such as 30 Hz) while the internal signal is sparsely acquired (such as 0.5 Hz or less). The internal signal is used to validate and update the internal/external correlation during treatment. Tumor positions are derived from the external signal based on the newly updated correlation. Two dynamic correlation updating algorithms are introduced. One is based on the motion amplitude and the other is based on the motion phase. Nine patients with synchronized internal/external motion signals are simulated retrospectively to evaluate the effectiveness of hybrid gating. The influences of different clinical conditions on hybrid gating, such as the size of gating windows, the optimal timing for internal signal acquisition and the acquisition frequency are investigated. The results demonstrate that dynamically updating the internal/external correlation in or around the gating window will reduce false positive with relatively diminished treatment efficiency. This improvement will benefit patients with mobile tumors, especially greater for early stage lung cancers, for which the tumors are less attached or freely floating in the lung.

Analyses and Measures of GPR Signal with Superimposed Noise

NASA Astrophysics Data System (ADS)

Chicarella, Simone; Ferrara, Vincenzo; D'Atanasio, Paolo; Frezza, Fabrizio; Pajewski, Lara; Pavoncello, Settimio; Prontera, Santo; Tedeschi, Nicola; Zambotti, Alessandro

2014-05-01

The influence of EM noises and environmental hard conditions on the GPR surveys has been examined analytically [1]. In the case of pulse radar GPR, many unwanted signals as stationary clutter, non-stationary clutter, random noise, and time jitter, influence the measurement signal. When GPR is motionless, stationary clutter is the most dominant signal component due to the reflections of static objects different from the investigated target, and to the direct antenna coupling. Moving objects like e.g. persons and vehicles, and the swaying of tree crown, produce non-stationary clutter. Device internal noise and narrowband jamming are e.g. two potential sources of random noises. Finally, trigger instabilities generate random jitter. In order to estimate the effective influence of these noise signal components, we organized some experimental setup of measurement. At first, we evaluated for the case of a GPR basic detection, simpler image processing of radargram. In the future, we foresee experimental measurements for detection of the Doppler frequency changes induced by movements of targets (like physiological movements of survivors under debris). We obtain image processing of radargram by using of GSSI SIR® 2000 GPR system together with the UWB UHF GPR-antenna (SUB-ECHO HBD 300, a model manufactured by Radarteam company). Our work includes both characterization of GPR signal without (or almost without) a superimposed noise, and the effect of jamming originated from the coexistence of a different radio signal. For characterizing GPR signal, we organized a measurement setup that includes the following instruments: mod. FSP 30 spectrum analyser by Rohde & Schwarz which operates in the frequency range 9 KHz - 30 GHz, mod. Sucoflex 104 cable by Huber Suhner (10 MHz - 18 GHz), and HL050 antenna by Rohde & Schwarz (bandwidth: from 850 MHz to 26.5 GHz). The next analysis of superimposed jamming will examine two different signal sources: by a cellular phone and by a

Velocity measurements of heterogeneous RBC flow in capillary vessels using dynamic laser speckle signal.

PubMed

Li, Chenxi; Wang, Ruikang

2017-04-01

We propose an approach to measure heterogeneous velocities of red blood cells (RBCs) in capillary vessels using full-field time-varying dynamic speckle signals. The approach utilizes a low coherent laser speckle imaging system to record the instantaneous speckle pattern, followed by an eigen-decomposition-based filtering algorithm to extract dynamic speckle signal due to the moving RBCs. The velocity of heterogeneous RBC flows is determined by cross-correlating the temporal dynamic speckle signals obtained at adjacent locations. We verify the approach by imaging mouse pinna in vivo, demonstrating its capability for full-field RBC flow mapping and quantifying flow pattern with high resolution. It is expected to investigate the dynamic action of RBCs flow in capillaries under physiological changes.

Velocity measurements of heterogeneous RBC flow in capillary vessels using dynamic laser speckle signal

PubMed Central

Li, Chenxi; Wang, Ruikang

2017-01-01

Abstract. We propose an approach to measure heterogeneous velocities of red blood cells (RBCs) in capillary vessels using full-field time-varying dynamic speckle signals. The approach utilizes a low coherent laser speckle imaging system to record the instantaneous speckle pattern, followed by an eigen-decomposition-based filtering algorithm to extract dynamic speckle signal due to the moving RBCs. The velocity of heterogeneous RBC flows is determined by cross-correlating the temporal dynamic speckle signals obtained at adjacent locations. We verify the approach by imaging mouse pinna in vivo, demonstrating its capability for full-field RBC flow mapping and quantifying flow pattern with high resolution. It is expected to investigate the dynamic action of RBCs flow in capillaries under physiological changes. PMID:28384709

Integrated omics analyses of retrograde signaling mutant delineate interrelated stress-response strata.

PubMed

Bjornson, Marta; Balcke, Gerd Ulrich; Xiao, Yanmei; de Souza, Amancio; Wang, Jin-Zheng; Zhabinskaya, Dina; Tagkopoulos, Ilias; Tissier, Alain; Dehesh, Katayoon

2017-07-01

To maintain homeostasis in the face of intrinsic and extrinsic insults, cells have evolved elaborate quality control networks to resolve damage at multiple levels. Interorganellar communication is a key requirement for this maintenance, however the underlying mechanisms of this communication have remained an enigma. Here we integrate the outcome of transcriptomic, proteomic, and metabolomics analyses of genotypes including ceh1, a mutant with constitutively elevated levels of both the stress-specific plastidial retrograde signaling metabolite methyl-erythritol cyclodiphosphate (MEcPP) and the defense hormone salicylic acid (SA), as well as the high MEcPP but SA deficient genotype ceh1/eds16, along with corresponding controls. Integration of multi-omic analyses enabled us to delineate the function of MEcPP from SA, and expose the compartmentalized role of this retrograde signaling metabolite in induction of distinct but interdependent signaling cascades instrumental in adaptive responses. Specifically, here we identify strata of MEcPP-sensitive stress-response cascades, among which we focus on selected pathways including organelle-specific regulation of jasmonate biosynthesis; simultaneous induction of synthesis and breakdown of SA; and MEcPP-mediated alteration of cellular redox status in particular glutathione redox balance. Collectively, these integrated multi-omic analyses provided a vehicle to gain an in-depth knowledge of genome-metabolism interactions, and to further probe the extent of these interactions and delineate their functional contributions. Through this approach we were able to pinpoint stress-mediated transcriptional and metabolic signatures and identify the downstream processes modulated by the independent or overlapping functions of MEcPP and SA in adaptive responses. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Ras signaling requires dynamic properties of Ets1 for phosphorylation-enhanced binding to coactivator CBP.

PubMed

Nelson, Mary L; Kang, Hyun-Seo; Lee, Gregory M; Blaszczak, Adam G; Lau, Desmond K W; McIntosh, Lawrence P; Graves, Barbara J

2010-06-01

Ras/MAPK signaling is often aberrantly activated in human cancers. The downstream effectors are transcription factors, including those encoded by the ETS gene family. Using cell-based assays and biophysical measurements, we have determined the mechanism by which Ras/MAPK signaling affects the function of Ets1 via phosphorylation of Thr38 and Ser41. These ERK2 phosphoacceptors lie within the unstructured N-terminal region of Ets1, immediately adjacent to the PNT domain. NMR spectroscopic analyses demonstrated that the PNT domain is a four-helix bundle (H2-H5), resembling the SAM domain, appended with two additional helices (H0-H1). Phosphorylation shifted a conformational equilibrium, displacing the dynamic helix H0 from the core bundle. The affinity of Ets1 for the TAZ1 (or CH1) domain of the coactivator CBP was enhanced 34-fold by phosphorylation, and this binding was sensitive to ionic strength. NMR-monitored titration experiments mapped the interaction surfaces of the TAZ1 domain and Ets1, the latter encompassing both the phosphoacceptors and PNT domain. Charge complementarity of these surfaces indicate that electrostatic forces act in concert with a conformational equilibrium to mediate phosphorylation effects. We conclude that the dynamic helical elements of Ets1, appended to a conserved structural core, constitute a phospho-switch that directs Ras/MAPK signaling to downstream changes in gene expression. This detailed structural and mechanistic information will guide strategies for targeting ETS proteins in human disease.

Separation of electrocardiographic from electromyographic signals using dynamic filtration.

PubMed

Christov, Ivaylo; Raikova, Rositsa; Angelova, Silvija

2018-07-01

Trunk muscle electromyographic (EMG) signals are often contaminated by the electrical activity of the heart. During low or moderate muscle force, these electrocardiographic (ECG) signals disturb the estimation of muscle activity. Butterworth high-pass filters with cut-off frequency of up to 60 Hz are often used to suppress the ECG signal. Such filters disturb the EMG signal in both frequency and time domain. A new method based on the dynamic application of Savitzky-Golay filter is proposed. EMG signals of three left trunk muscles and pure ECG signal were recorded during different motor tasks. The efficiency of the method was tested and verified both with the experimental EMG signals and with modeled signals obtained by summing the pure ECG signal with EMG signals at different levels of signal-to-noise ratio. The results were compared with those obtained by application of high-pass, 4th order Butterworth filter with cut-off frequency of 30 Hz. The suggested method is separating the EMG signal from the ECG signal without EMG signal distortion across its entire frequency range regardless of amplitudes. Butterworth filter suppresses the signals in the 0-30 Hz range thus preventing the low-frequency analysis of the EMG signal. An additional disadvantage is that it passes high-frequency ECG signal components which is apparent at equal and higher amplitudes of the ECG signal as compared to the EMG signal. The new method was also successfully verified with abnormal ECG signals. Copyright © 2018. Published by Elsevier Ltd.

Artificial Neural Network-Based Early-Age Concrete Strength Monitoring Using Dynamic Response Signals.

PubMed

Kim, Junkyeong; Lee, Chaggil; Park, Seunghee

2017-06-07

Concrete is one of the most common materials used to construct a variety of civil infrastructures. However, since concrete might be susceptible to brittle fracture, it is essential to confirm the strength of concrete at the early-age stage of the curing process to prevent unexpected collapse. To address this issue, this study proposes a novel method to estimate the early-age strength of concrete, by integrating an artificial neural network algorithm with a dynamic response measurement of the concrete material. The dynamic response signals of the concrete, including both electromechanical impedances and guided ultrasonic waves, are obtained from an embedded piezoelectric sensor module. The cross-correlation coefficient of the electromechanical impedance signals and the amplitude of the guided ultrasonic wave signals are selected to quantify the variation in dynamic responses according to the strength of the concrete. Furthermore, an artificial neural network algorithm is used to verify a relationship between the variation in dynamic response signals and concrete strength. The results of an experimental study confirm that the proposed approach can be effectively applied to estimate the strength of concrete material from the early-age stage of the curing process.

Artificial Neural Network-Based Early-Age Concrete Strength Monitoring Using Dynamic Response Signals

PubMed Central

Kim, Junkyeong; Lee, Chaggil; Park, Seunghee

2017-01-01

Concrete is one of the most common materials used to construct a variety of civil infrastructures. However, since concrete might be susceptible to brittle fracture, it is essential to confirm the strength of concrete at the early-age stage of the curing process to prevent unexpected collapse. To address this issue, this study proposes a novel method to estimate the early-age strength of concrete, by integrating an artificial neural network algorithm with a dynamic response measurement of the concrete material. The dynamic response signals of the concrete, including both electromechanical impedances and guided ultrasonic waves, are obtained from an embedded piezoelectric sensor module. The cross-correlation coefficient of the electromechanical impedance signals and the amplitude of the guided ultrasonic wave signals are selected to quantify the variation in dynamic responses according to the strength of the concrete. Furthermore, an artificial neural network algorithm is used to verify a relationship between the variation in dynamic response signals and concrete strength. The results of an experimental study confirm that the proposed approach can be effectively applied to estimate the strength of concrete material from the early-age stage of the curing process. PMID:28590456

Field Crickets Compensate for Unattractive Static Long-Distance Call Components by Increasing Dynamic Signalling Effort

PubMed Central

McAuley, Emily M.

2016-01-01

The evolution of multiple sexual signals presents a dilemma since individuals selecting a mate should pay attention to the most honest signal and ignore the rest; however, multiple signals may evolve if, together, they provide more information to the receiver than either one would alone. Static and dynamic signals, for instance, can act as multiple messages, providing information on different aspects of signaller quality that reflect condition at different time scales. While the nature of static signals makes them difficult or impossible for individuals to augment, dynamic signals are much more susceptible to temporary fluctuations in effort. We investigated whether male Texas field crickets, Gryllus texensis, that produce unattractive static signals compensate by dynamically increasing their calling effort. Our findings lend partial support to the compensation hypothesis, as males that called at unattractive carrier frequencies (a static trait) spent more time calling each night (a dynamic trait). Interestingly, this finding was most pronounced in males that called with attractive pulse characteristics (static traits) but did not occur in males that called with unattractive pulse characteristics. Males that signalled with unattractive pulse characteristics (duration and pause) spent less time calling through the night. Our correlative findings on wild caught males suggest that only males that signal with attractive pulse characteristics may be able to afford to pay the costs of both trait exaggeration and increased calling effort to compensate for poor carrier frequencies. PMID:27936045

Field Crickets Compensate for Unattractive Static Long-Distance Call Components by Increasing Dynamic Signalling Effort.

PubMed

McAuley, Emily M; Bertram, Susan M

2016-01-01

The evolution of multiple sexual signals presents a dilemma since individuals selecting a mate should pay attention to the most honest signal and ignore the rest; however, multiple signals may evolve if, together, they provide more information to the receiver than either one would alone. Static and dynamic signals, for instance, can act as multiple messages, providing information on different aspects of signaller quality that reflect condition at different time scales. While the nature of static signals makes them difficult or impossible for individuals to augment, dynamic signals are much more susceptible to temporary fluctuations in effort. We investigated whether male Texas field crickets, Gryllus texensis, that produce unattractive static signals compensate by dynamically increasing their calling effort. Our findings lend partial support to the compensation hypothesis, as males that called at unattractive carrier frequencies (a static trait) spent more time calling each night (a dynamic trait). Interestingly, this finding was most pronounced in males that called with attractive pulse characteristics (static traits) but did not occur in males that called with unattractive pulse characteristics. Males that signalled with unattractive pulse characteristics (duration and pause) spent less time calling through the night. Our correlative findings on wild caught males suggest that only males that signal with attractive pulse characteristics may be able to afford to pay the costs of both trait exaggeration and increased calling effort to compensate for poor carrier frequencies.

Dynamic characteristics of laser Doppler flowmetry signals obtained in response to a local and progressive pressure applied on diabetic and healthy subjects

NASA Astrophysics Data System (ADS)

Humeau, Anne; Koitka, Audrey; Abraham, Pierre; Saumet, Jean-Louis; L'Huillier, Jean-Pierre

2004-09-01

In the biomedical field, the laser Doppler flowmetry (LDF) technique is a non-invasive method to monitor skin perfusion. On the skin of healthy humans, LDF signals present a significant transient increase in response to a local and progressive pressure application. This vasodilatory reflex response may have important implications for cutaneous pathologies involved in various neurological diseases and in the pathophysiology of decubitus ulcers. The present work analyses the dynamic characteristics of these signals on young type 1 diabetic patients, and on healthy age-matched subjects. To obtain accurate dynamic characteristic values, a de-noising wavelet-based algorithm is first applied to LDF signals. All the de-noised signals are then normalised to the same value. The blood flow peak and the time to reach this peak are then calculated on each computed signal. The results show that a large vasodilation is present on signals of healthy subjects. The mean peak occurs at a pressure of 3.2 kPa approximately. However, a vasodilation of limited amplitude appears on type 1 diabetic patients. The maximum value is visualised, on the average, when the pressure is 1.1 kPa. The inability for diabetic patients to increase largely their cutaneous blood flow may bring explanations to foot ulcers.

Detection of allosteric signal transmission by information-theoretic analysis of protein dynamics

PubMed Central

Pandini, Alessandro; Fornili, Arianna; Fraternali, Franca; Kleinjung, Jens

2012-01-01

Allostery offers a highly specific way to modulate protein function. Therefore, understanding this mechanism is of increasing interest for protein science and drug discovery. However, allosteric signal transmission is difficult to detect experimentally and to model because it is often mediated by local structural changes propagating along multiple pathways. To address this, we developed a method to identify communication pathways by an information-theoretical analysis of molecular dynamics simulations. Signal propagation was described as information exchange through a network of correlated local motions, modeled as transitions between canonical states of protein fragments. The method was used to describe allostery in two-component regulatory systems. In particular, the transmission from the allosteric site to the signaling surface of the receiver domain NtrC was shown to be mediated by a layer of hub residues. The location of hubs preferentially connected to the allosteric site was found in close agreement with key residues experimentally identified as involved in the signal transmission. The comparison with the networks of the homologues CheY and FixJ highlighted similarities in their dynamics. In particular, we showed that a preorganized network of fragment connections between the allosteric and functional sites exists already in the inactive state of all three proteins.—Pandini, A., Fornili, A., Fraternali, F., Kleinjung, J. Detection of allosteric signal transmission by information-theoretic analysis of protein dynamics. PMID:22071506

Signal Processing for Determining Water Height in Steam Pipes with Dynamic Surface Conditions

NASA Technical Reports Server (NTRS)

Lih, Shyh-Shiuh; Lee, Hyeong Jae; Bar-Cohen, Yoseph

2015-01-01

An enhanced signal processing method based on the filtered Hilbert envelope of the auto-correlation function of the wave signal has been developed to monitor the height of condensed water through the steel wall of steam pipes with dynamic surface conditions. The developed signal processing algorithm can also be used to estimate the thickness of the pipe to determine the cut-off frequency for the low pass filter frequency of the Hilbert Envelope. Testing and analysis results by using the developed technique for dynamic surface conditions are presented. A multiple array of transducers setup and methodology are proposed for both the pulse-echo and pitch-catch signals to monitor the fluctuation of the water height due to disturbance, water flow, and other anomaly conditions.

Improved Protein Arrays for Quantitative Systems Analysis of the Dynamics of Signaling Pathway Interactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Chin-Rang

Astronauts and workers in nuclear plants who repeatedly exposed to low doses of ionizing radiation (IR, <10 cGy) are likely to incur specific changes in signal transduction and gene expression in various tissues of their body. Remarkable advances in high throughput genomics and proteomics technologies enable researchers to broaden their focus from examining single gene/protein kinetics to better understanding global gene/protein expression profiling and biological pathway analyses, namely Systems Biology. An ultimate goal of systems biology is to develop dynamic mathematical models of interacting biological systems capable of simulating living systems in a computer. This Glue Grant is to complementmore » Dr. Boothman’s existing DOE grant (No. DE-FG02-06ER64186) entitled “The IGF1/IGF-1R-MAPK-Secretory Clusterin (sCLU) Pathway: Mediator of a Low Dose IR-Inducible Bystander Effect” to develop sensitive and quantitative proteomic technology that suitable for low dose radiobiology researches. An improved version of quantitative protein array platform utilizing linear Quantum dot signaling for systematically measuring protein levels and phosphorylation states for systems biology modeling is presented. The signals are amplified by a confocal laser Quantum dot scanner resulting in ~1000-fold more sensitivity than traditional Western blots and show the good linearity that is impossible for the signals of HRP-amplification. Therefore this improved protein array technology is suitable to detect weak responses of low dose radiation. Software is developed to facilitate the quantitative readout of signaling network activities. Kinetics of EGFRvIII mutant signaling was analyzed to quantify cross-talks between EGFR and other signaling pathways.« less

The signaling petri net-based simulator: a non-parametric strategy for characterizing the dynamics of cell-specific signaling networks.

PubMed

Ruths, Derek; Muller, Melissa; Tseng, Jen-Te; Nakhleh, Luay; Ram, Prahlad T

2008-02-29

Reconstructing cellular signaling networks and understanding how they work are major endeavors in cell biology. The scale and complexity of these networks, however, render their analysis using experimental biology approaches alone very challenging. As a result, computational methods have been developed and combined with experimental biology approaches, producing powerful tools for the analysis of these networks. These computational methods mostly fall on either end of a spectrum of model parameterization. On one end is a class of structural network analysis methods; these typically use the network connectivity alone to generate hypotheses about global properties. On the other end is a class of dynamic network analysis methods; these use, in addition to the connectivity, kinetic parameters of the biochemical reactions to predict the network's dynamic behavior. These predictions provide detailed insights into the properties that determine aspects of the network's structure and behavior. However, the difficulty of obtaining numerical values of kinetic parameters is widely recognized to limit the applicability of this latter class of methods. Several researchers have observed that the connectivity of a network alone can provide significant insights into its dynamics. Motivated by this fundamental observation, we present the signaling Petri net, a non-parametric model of cellular signaling networks, and the signaling Petri net-based simulator, a Petri net execution strategy for characterizing the dynamics of signal flow through a signaling network using token distribution and sampling. The result is a very fast method, which can analyze large-scale networks, and provide insights into the trends of molecules' activity-levels in response to an external stimulus, based solely on the network's connectivity. We have implemented the signaling Petri net-based simulator in the PathwayOracle toolkit, which is publicly available at http://bioinfo.cs.rice.edu/pathwayoracle. Using

The Signaling Petri Net-Based Simulator: A Non-Parametric Strategy for Characterizing the Dynamics of Cell-Specific Signaling Networks

PubMed Central

Ruths, Derek; Muller, Melissa; Tseng, Jen-Te; Nakhleh, Luay; Ram, Prahlad T.

2008-01-01

Reconstructing cellular signaling networks and understanding how they work are major endeavors in cell biology. The scale and complexity of these networks, however, render their analysis using experimental biology approaches alone very challenging. As a result, computational methods have been developed and combined with experimental biology approaches, producing powerful tools for the analysis of these networks. These computational methods mostly fall on either end of a spectrum of model parameterization. On one end is a class of structural network analysis methods; these typically use the network connectivity alone to generate hypotheses about global properties. On the other end is a class of dynamic network analysis methods; these use, in addition to the connectivity, kinetic parameters of the biochemical reactions to predict the network's dynamic behavior. These predictions provide detailed insights into the properties that determine aspects of the network's structure and behavior. However, the difficulty of obtaining numerical values of kinetic parameters is widely recognized to limit the applicability of this latter class of methods. Several researchers have observed that the connectivity of a network alone can provide significant insights into its dynamics. Motivated by this fundamental observation, we present the signaling Petri net, a non-parametric model of cellular signaling networks, and the signaling Petri net-based simulator, a Petri net execution strategy for characterizing the dynamics of signal flow through a signaling network using token distribution and sampling. The result is a very fast method, which can analyze large-scale networks, and provide insights into the trends of molecules' activity-levels in response to an external stimulus, based solely on the network's connectivity. We have implemented the signaling Petri net-based simulator in the PathwayOracle toolkit, which is publicly available at http://bioinfo.cs.rice.edu/pathwayoracle. Using

Analysis of Coherent Phonon Signals by Sparsity-promoting Dynamic Mode Decomposition

NASA Astrophysics Data System (ADS)

Murata, Shin; Aihara, Shingo; Tokuda, Satoru; Iwamitsu, Kazunori; Mizoguchi, Kohji; Akai, Ichiro; Okada, Masato

2018-05-01

We propose a method to decompose normal modes in a coherent phonon (CP) signal by sparsity-promoting dynamic mode decomposition. While the CP signals can be modeled as the sum of finite number of damped oscillators, the conventional method such as Fourier transform adopts continuous bases in a frequency domain. Thus, the uncertainty of frequency appears and it is difficult to estimate the initial phase. Moreover, measurement artifacts are imposed on the CP signal and deforms the Fourier spectrum. In contrast, the proposed method can separate the signal from the artifact precisely and can successfully estimate physical properties of the normal modes.

Aggregation Dynamics Using Phase Wave Signals and Branching Patterns

NASA Astrophysics Data System (ADS)

Sakaguchi, Hidetsugu; Kusagaki, Takuma

2016-09-01

The aggregation dynamics of slime mold is studied using coupled equations of phase ϕ and cell concentration n. Phase waves work as tactic signals for aggregation. Branching structures appear during the aggregation. A stationary branching pattern appears like a river network, if cells are uniformly supplied into the system.

Collaborative Signaling of Informational Structures by Dynamic Speech Rate.

ERIC Educational Resources Information Center

Koiso, Hanae; Shimojima, Atsushi; Katagiri, Yasuhiro

1998-01-01

Investigated the functions of dynamic speech rates as contextualization cues in conversational Japanese, examining five spontaneous task-oriented dialogs and analyzing the potential of speech-rate changes in signaling the structure of the information being exchanged. Results found a correlation between speech decelerations and the openings of new…

Dynamic Testing of Signal Transduction Deregulation During Breast Cancer Initiation

DTIC Science & Technology

2012-07-01

Std. Z39.18 Victoria Seewaldt, M.D. Dynamic Testing of Signal Transduction Deregulation During Breast Cancer Initiation Duke University Durham...attomole- zeptomole range. Internal dilution curves insure a high-dynamic calibration range. DU -26 8L DU -26 6L DU -29 5R DU -22 9.2 L DU...3: Nanobiosensor technology is translated to test for pathway deregulation in RPFNA cytology obtained from 10 high-risk women with cytological

Structural analysis of eyespots: dynamics of morphogenic signals that govern elemental positions in butterfly wings

PubMed Central

2012-01-01

Background To explain eyespot colour-pattern determination in butterfly wings, the induction model has been discussed based on colour-pattern analyses of various butterfly eyespots. However, a detailed structural analysis of eyespots that can serve as a foundation for future studies is still lacking. In this study, fundamental structural rules related to butterfly eyespots are proposed, and the induction model is elaborated in terms of the possible dynamics of morphogenic signals involved in the development of eyespots and parafocal elements (PFEs) based on colour-pattern analysis of the nymphalid butterfly Junonia almana. Results In a well-developed eyespot, the inner black core ring is much wider than the outer black ring; this is termed the inside-wide rule. It appears that signals are wider near the focus of the eyespot and become narrower as they expand. Although fundamental signal dynamics are likely to be based on a reaction-diffusion mechanism, they were described well mathematically as a type of simple uniformly decelerated motion in which signals associated with the outer and inner black rings of eyespots and PFEs are released at different time points, durations, intervals, and initial velocities into a two-dimensional field of fundamentally uniform or graded resistance; this produces eyespots and PFEs that are diverse in size and structure. The inside-wide rule, eyespot distortion, structural differences between small and large eyespots, and structural changes in eyespots and PFEs in response to physiological treatments were explained well using mathematical simulations. Natural colour patterns and previous experimental findings that are not easily explained by the conventional gradient model were also explained reasonably well by the formal mathematical simulations performed in this study. Conclusions In a mode free from speculative molecular interactions, the present study clarifies fundamental structural rules related to butterfly eyespots, delineates

Structural analysis of eyespots: dynamics of morphogenic signals that govern elemental positions in butterfly wings.

PubMed

Otaki, Joji M

2012-03-13

To explain eyespot colour-pattern determination in butterfly wings, the induction model has been discussed based on colour-pattern analyses of various butterfly eyespots. However, a detailed structural analysis of eyespots that can serve as a foundation for future studies is still lacking. In this study, fundamental structural rules related to butterfly eyespots are proposed, and the induction model is elaborated in terms of the possible dynamics of morphogenic signals involved in the development of eyespots and parafocal elements (PFEs) based on colour-pattern analysis of the nymphalid butterfly Junonia almana. In a well-developed eyespot, the inner black core ring is much wider than the outer black ring; this is termed the inside-wide rule. It appears that signals are wider near the focus of the eyespot and become narrower as they expand. Although fundamental signal dynamics are likely to be based on a reaction-diffusion mechanism, they were described well mathematically as a type of simple uniformly decelerated motion in which signals associated with the outer and inner black rings of eyespots and PFEs are released at different time points, durations, intervals, and initial velocities into a two-dimensional field of fundamentally uniform or graded resistance; this produces eyespots and PFEs that are diverse in size and structure. The inside-wide rule, eyespot distortion, structural differences between small and large eyespots, and structural changes in eyespots and PFEs in response to physiological treatments were explained well using mathematical simulations. Natural colour patterns and previous experimental findings that are not easily explained by the conventional gradient model were also explained reasonably well by the formal mathematical simulations performed in this study. In a mode free from speculative molecular interactions, the present study clarifies fundamental structural rules related to butterfly eyespots, delineates a theoretical basis for the

Real-time Nyquist signaling with dynamic precision and flexible non-integer oversampling.

PubMed

Schmogrow, R; Meyer, M; Schindler, P C; Nebendahl, B; Dreschmann, M; Meyer, J; Josten, A; Hillerkuss, D; Ben-Ezra, S; Becker, J; Koos, C; Freude, W; Leuthold, J

2014-01-13

We demonstrate two efficient processing techniques for Nyquist signals, namely computation of signals using dynamic precision as well as arbitrary rational oversampling factors. With these techniques along with massively parallel processing it becomes possible to generate and receive high data rate Nyquist signals with flexible symbol rates and bandwidths, a feature which is highly desirable for novel flexgrid networks. We achieved maximum bit rates of 252 Gbit/s in real-time.

Dynamic regulation of GDP binding to G proteins revealed by magnetic field-dependent NMR relaxation analyses

PubMed Central

Toyama, Yuki; Kano, Hanaho; Mase, Yoko; Yokogawa, Mariko; Osawa, Masanori; Shimada, Ichio

2017-01-01

Heterotrimeric guanine-nucleotide-binding proteins (G proteins) serve as molecular switches in signalling pathways, by coupling the activation of cell surface receptors to intracellular responses. Mutations in the G protein α-subunit (Gα) that accelerate guanosine diphosphate (GDP) dissociation cause hyperactivation of the downstream effector proteins, leading to oncogenesis. However, the structural mechanism of the accelerated GDP dissociation has remained unclear. Here, we use magnetic field-dependent nuclear magnetic resonance relaxation analyses to investigate the structural and dynamic properties of GDP bound Gα on a microsecond timescale. We show that Gα rapidly exchanges between a ground-state conformation, which tightly binds to GDP and an excited conformation with reduced GDP affinity. The oncogenic D150N mutation accelerates GDP dissociation by shifting the equilibrium towards the excited conformation. PMID:28223697

Dynamic regulation of GDP binding to G proteins revealed by magnetic field-dependent NMR relaxation analyses.

PubMed

Toyama, Yuki; Kano, Hanaho; Mase, Yoko; Yokogawa, Mariko; Osawa, Masanori; Shimada, Ichio

2017-02-22

Heterotrimeric guanine-nucleotide-binding proteins (G proteins) serve as molecular switches in signalling pathways, by coupling the activation of cell surface receptors to intracellular responses. Mutations in the G protein α-subunit (Gα) that accelerate guanosine diphosphate (GDP) dissociation cause hyperactivation of the downstream effector proteins, leading to oncogenesis. However, the structural mechanism of the accelerated GDP dissociation has remained unclear. Here, we use magnetic field-dependent nuclear magnetic resonance relaxation analyses to investigate the structural and dynamic properties of GDP bound Gα on a microsecond timescale. We show that Gα rapidly exchanges between a ground-state conformation, which tightly binds to GDP and an excited conformation with reduced GDP affinity. The oncogenic D150N mutation accelerates GDP dissociation by shifting the equilibrium towards the excited conformation.

Detection of a dynamic topography signal in last interglacial sea-level records

PubMed Central

Austermann, Jacqueline; Mitrovica, Jerry X.; Huybers, Peter; Rovere, Alessio

2017-01-01

Estimating minimum ice volume during the last interglacial based on local sea-level indicators requires that these indicators are corrected for processes that alter local sea level relative to the global average. Although glacial isostatic adjustment is generally accounted for, global scale dynamic changes in topography driven by convective mantle flow are generally not considered. We use numerical models of mantle flow to quantify vertical deflections caused by dynamic topography and compare predictions at passive margins to a globally distributed set of last interglacial sea-level markers. The deflections predicted as a result of dynamic topography are significantly correlated with marker elevations (>95% probability) and are consistent with construction and preservation attributes across marker types. We conclude that a dynamic topography signal is present in the elevation of last interglacial sea-level records and that the signal must be accounted for in any effort to determine peak global mean sea level during the last interglacial to within an accuracy of several meters. PMID:28695210

Dynamic pathway modeling of signal transduction networks: a domain-oriented approach.

PubMed

Conzelmann, Holger; Gilles, Ernst-Dieter

2008-01-01

Mathematical models of biological processes become more and more important in biology. The aim is a holistic understanding of how processes such as cellular communication, cell division, regulation, homeostasis, or adaptation work, how they are regulated, and how they react to perturbations. The great complexity of most of these processes necessitates the generation of mathematical models in order to address these questions. In this chapter we provide an introduction to basic principles of dynamic modeling and highlight both problems and chances of dynamic modeling in biology. The main focus will be on modeling of s transduction pathways, which requires the application of a special modeling approach. A common pattern, especially in eukaryotic signaling systems, is the formation of multi protein signaling complexes. Even for a small number of interacting proteins the number of distinguishable molecular species can be extremely high. This combinatorial complexity is due to the great number of distinct binding domains of many receptors and scaffold proteins involved in signal transduction. However, these problems can be overcome using a new domain-oriented modeling approach, which makes it possible to handle complex and branched signaling pathways.

Smad Signaling Dynamics: Insights from a Parsimonious Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wiley, H. S.; Shankaran, Harish

2008-09-09

The molecular mechanisms that transmit information from cell surface receptors to the nucleus are exceedingly complex; thus, much effort has been expended in developing computational models to understand these processes. A recent study on modeling the nuclear-cytoplasmic shuttling of Smad2-Smad4 complexes in response to transforming growth factor β (TGF-β) receptor activation has provided substantial insight into how this signaling network translates the degree of TGF-β receptor activation (input) into the amount of nuclear Smad2-Smad4 complexes (output). The study addressed this question by combining a simple, mechanistic model with targeted experiments, an approach that proved particularly powerful for exploring the fundamentalmore » properties of a complex signaling network. The mathematical model revealed that Smad nuclear-cytoplasmic dynamics enables a proportional, but time-delayed coupling between the input and the output. As a result, the output can faithfully track gradual changes in the input, while the rapid input fluctuations that constitute signaling noise are dampened out.« less

Studying Cellular Signal Transduction with OMIC Technologies.

PubMed

Landry, Benjamin D; Clarke, David C; Lee, Michael J

2015-10-23

In the gulf between genotype and phenotype exists proteins and, in particular, protein signal transduction systems. These systems use a relatively limited parts list to respond to a much longer list of extracellular, environmental, and/or mechanical cues with rapidity and specificity. Most signaling networks function in a highly non-linear and often contextual manner. Furthermore, these processes occur dynamically across space and time. Because of these complexities, systems and "OMIC" approaches are essential for the study of signal transduction. One challenge in using OMIC-scale approaches to study signaling is that the "signal" can take different forms in different situations. Signals are encoded in diverse ways such as protein-protein interactions, enzyme activities, localizations, or post-translational modifications to proteins. Furthermore, in some cases, signals may be encoded only in the dynamics, duration, or rates of change of these features. Accordingly, systems-level analyses of signaling may need to integrate multiple experimental and/or computational approaches. As the field has progressed, the non-triviality of integrating experimental and computational analyses has become apparent. Successful use of OMIC methods to study signaling will require the "right" experiments and the "right" modeling approaches, and it is critical to consider both in the design phase of the project. In this review, we discuss common OMIC and modeling approaches for studying signaling, emphasizing the philosophical and practical considerations for effectively merging these two types of approaches to maximize the probability of obtaining reliable and novel insights into signaling biology. Copyright © 2015 Elsevier Ltd. All rights reserved.

A quantitative image cytometry technique for time series or population analyses of signaling networks.

PubMed

Ozaki, Yu-ichi; Uda, Shinsuke; Saito, Takeshi H; Chung, Jaehoon; Kubota, Hiroyuki; Kuroda, Shinya

2010-04-01

Modeling of cellular functions on the basis of experimental observation is increasingly common in the field of cellular signaling. However, such modeling requires a large amount of quantitative data of signaling events with high spatio-temporal resolution. A novel technique which allows us to obtain such data is needed for systems biology of cellular signaling. We developed a fully automatable assay technique, termed quantitative image cytometry (QIC), which integrates a quantitative immunostaining technique and a high precision image-processing algorithm for cell identification. With the aid of an automated sample preparation system, this device can quantify protein expression, phosphorylation and localization with subcellular resolution at one-minute intervals. The signaling activities quantified by the assay system showed good correlation with, as well as comparable reproducibility to, western blot analysis. Taking advantage of the high spatio-temporal resolution, we investigated the signaling dynamics of the ERK pathway in PC12 cells. The QIC technique appears as a highly quantitative and versatile technique, which can be a convenient replacement for the most conventional techniques including western blot, flow cytometry and live cell imaging. Thus, the QIC technique can be a powerful tool for investigating the systems biology of cellular signaling.

High-throughput microfluidics to control and measure signaling dynamics in single yeast cells

PubMed Central

Hansen, Anders S.; Hao, Nan; O'Shea, Erin K.

2015-01-01

Microfluidics coupled to quantitative time-lapse fluorescence microscopy is transforming our ability to control, measure, and understand signaling dynamics in single living cells. Here we describe a pipeline that incorporates multiplexed microfluidic cell culture, automated programmable fluid handling for cell perturbation, quantitative time-lapse microscopy, and computational analysis of time-lapse movies. We illustrate how this setup can be used to control the nuclear localization of the budding yeast transcription factor Msn2. Using this protocol, we generate oscillations of Msn2 localization and measure the dynamic gene expression response of individual genes in single cells. The protocol allows a single researcher to perform up to 20 different experiments in a single day, whilst collecting data for thousands of single cells. Compared to other protocols, the present protocol is relatively easy to adopt and higher-throughput. The protocol can be widely used to control and monitor single-cell signaling dynamics in other signal transduction systems in microorganisms. PMID:26158443

Analysis of a dynamic model of guard cell signaling reveals the stability of signal propagation

NASA Astrophysics Data System (ADS)

Gan, Xiao; Albert, RéKa

Analyzing the long-term behaviors (attractors) of dynamic models of biological systems can provide valuable insight into biological phenotypes and their stability. We identified the long-term behaviors of a multi-level, 70-node discrete dynamic model of the stomatal opening process in plants. We reduce the model's huge state space by reducing unregulated nodes and simple mediator nodes, and by simplifying the regulatory functions of selected nodes while keeping the model consistent with experimental observations. We perform attractor analysis on the resulting 32-node reduced model by two methods: 1. converting it into a Boolean model, then applying two attractor-finding algorithms; 2. theoretical analysis of the regulatory functions. We conclude that all nodes except two in the reduced model have a single attractor; and only two nodes can admit oscillations. The multistability or oscillations do not affect the stomatal opening level in any situation. This conclusion applies to the original model as well in all the biologically meaningful cases. We further demonstrate the robustness of signal propagation by showing that a large percentage of single-node knockouts does not affect the stomatal opening level. Thus, we conclude that the complex structure of this signal transduction network provides multiple information propagation pathways while not allowing extensive multistability or oscillations, resulting in robust signal propagation. Our innovative combination of methods offers a promising way to analyze multi-level models.

Mutational Analyses of HAMP Helices Suggest a Dynamic Bundle Model of Input-Output Signaling in Chemoreceptors

PubMed Central

Zhou, Qin; Ames, Peter; Parkinson, John S.

2009-01-01

SUMMARY To test the gearbox model of HAMP signaling in the E. coli serine receptor, Tsr, we generated a series of amino acid replacements at each residue of the AS1 and AS2 helices. The residues most critical for Tsr function defined hydrophobic packing faces consistent with a 4-helix bundle. Suppression patterns of helix lesions conformed to the the predicted packing layers in the bundle. Although the properties and patterns of most AS1 and AS2 lesions were consistent with both proposed gearbox structures, some mutational features specifically indicate the functional importance of an x-da bundle over an alternative a-d bundle. These genetic data suggest that HAMP signaling could simply involve changes in the stability of its x-da bundle. We propose that Tsr HAMP controls output signals by modulating destabilizing phase clashes between the AS2 helices and the adjoining kinase control helices. Our model further proposes that chemoeffectors regulate HAMP bundle stability through a control cable connection between the transmembrane segments and AS1 helices. Attractant stimuli, which cause inward piston displacements in chemoreceptors, should reduce cable tension, thereby stabilizing the HAMP bundle. This study shows how transmembrane signaling and HAMP input-output control could occur without the helix rotations central to the gearbox model. PMID:19656294

Dynamics and control of the ERK signaling pathway: Sensitivity, bistability, and oscillations.

PubMed

Arkun, Yaman; Yasemi, Mohammadreza

2018-01-01

Cell signaling is the process by which extracellular information is transmitted into the cell to perform useful biological functions. The ERK (extracellular-signal-regulated kinase) signaling controls several cellular processes such as cell growth, proliferation, differentiation and apoptosis. The ERK signaling pathway considered in this work starts with an extracellular stimulus and ends with activated (double phosphorylated) ERK which gets translocated into the nucleus. We model and analyze this complex pathway by decomposing it into three functional subsystems. The first subsystem spans the initial part of the pathway from the extracellular growth factor to the formation of the SOS complex, ShC-Grb2-SOS. The second subsystem includes the activation of Ras which is mediated by the SOS complex. This is followed by the MAPK subsystem (or the Raf-MEK-ERK pathway) which produces the double phosphorylated ERK upon being activated by Ras. Although separate models exist in the literature at the subsystems level, a comprehensive model for the complete system including the important regulatory feedback loops is missing. Our dynamic model combines the existing subsystem models and studies their steady-state and dynamic interactions under feedback. We establish conditions under which bistability and oscillations exist for this important pathway. In particular, we show how the negative and positive feedback loops affect the dynamic characteristics that determine the cellular outcome.

Regulation of Dynamic Behavior of Retinal Microglia by CX3CR1 Signaling

PubMed Central

Liang, Katharine J.; Lee, Jung Eun; Wang, Yunqing D.; Ma, Wenxin; Fontainhas, Aurora M.; Fariss, Robert N.; Wong, Wai T.

2009-01-01

PURPOSE Microglia in the central nervous system display a marked structural dynamism in their processes in the resting state. This dynamic behavior, which may play a constitutive surveying role in the uninjured neural parenchyma, is also highly responsive to tissue injury. The role of CX3CR1, a chemokine receptor expressed in microglia, in regulating microglia morphology and dynamic behavior in the resting state and after laser-induced focal injury was examined. METHODS Time-lapse confocal imaging of retinal explants was used to evaluate the dynamic behavior of retinal microglia labeled with green fluorescent protein (GFP). Transgenic mice in which CX3CR1 signaling was ablated (CX3CR1GFP/GFP/CX3CR1−/−) and preserved (CX3CR1+/GFP/CX3CR1+/−) were used. RESULTS Retinal microglial density, distribution, cellular morphology, and overall retinal tissue anatomy were not altered in young CX3CR1−/− animals. In the absence of CX3CR1, retinal microglia continued to exhibit dynamic motility in their processes. However, rates of process movement were significantly decreased, both under resting conditions and in response to tissue injury. In addition, microglia migration occurring in response to focal laser injury was also significantly slowed in microglia lacking CX3CR1. CONCLUSIONS CX3CR1 signaling in retinal microglia, though not absolutely required for the presence of microglial dynamism, plays a role in potentiating the rate of retinal microglial process dynamism and cellular migration. CX3CL1 signaling from retinal neurons and endothelial cells likely modulates dynamic microglia behavior so as to influence the level of microglial surveillance under basal conditions and the rate of dynamic behavior in response to tissue injury. PMID:19443728

The dynamics of color signals in male threespine sticklebacks Gasterosteus aculeatus.

PubMed

Hiermes, Meike; Rick, Ingolf P; Mehlis, Marion; Bakker, Theo C M

2016-02-01

Body coloration and color patterns are ubiquitous throughout the animal kingdom and vary between and within species. Recent studies have dealt with individual dynamics of various aspects of coloration, as it is in many cases a flexible trait and changes in color expression may be context-dependent. During the reproductive phase, temporal changes of coloration in the visible spectral range (400-700 nm) have been shown for many animals but corresponding changes in the ultraviolet (UV) waveband (300-400 nm) have rarely been studied. Threespine stickleback Gasterosteus aculeatus males develop conspicuous orange-red breeding coloration combined with UV reflectance in the cheek region. We investigated dynamics of color patterns including UV throughout a male breeding cycle, as well as short-term changes in coloration in response to a computer-animated rival using reflectance spectrophotometry and visual modeling, to estimate how colors would be perceived by conspecifics. We found the orange-red component of coloration to vary during the breeding cycle with respect to hue ( theta /R50) and intensity (achieved chroma/red chroma). Furthermore, color intensity in the orange-red spectral part (achieved chroma) tended to be increased after the presentation of an artificial rival. Dynamic changes in specific measures of hue and intensity in the UV waveband were not found. In general, the orange-red component of the signal seems to be dynamic with respect to color intensity and hue. This accounts in particular for color changes during the breeding cycle, presumably to signal reproductive status, and with limitations as well in the intrasexual context, most likely to signal dominance or inferiority.

Extracting protein dynamics information from overlapped NMR signals using relaxation dispersion difference NMR spectroscopy.

PubMed

Konuma, Tsuyoshi; Harada, Erisa; Sugase, Kenji

2015-12-01

Protein dynamics plays important roles in many biological events, such as ligand binding and enzyme reactions. NMR is mostly used for investigating such protein dynamics in a site-specific manner. Recently, NMR has been actively applied to large proteins and intrinsically disordered proteins, which are attractive research targets. However, signal overlap, which is often observed for such proteins, hampers accurate analysis of NMR data. In this study, we have developed a new methodology called relaxation dispersion difference that can extract conformational exchange parameters from overlapped NMR signals measured using relaxation dispersion spectroscopy. In relaxation dispersion measurements, the signal intensities of fluctuating residues vary according to the Carr-Purcell-Meiboon-Gill pulsing interval, whereas those of non-fluctuating residues are constant. Therefore, subtraction of each relaxation dispersion spectrum from that with the highest signal intensities, measured at the shortest pulsing interval, leaves only the signals of the fluctuating residues. This is the principle of the relaxation dispersion difference method. This new method enabled us to extract exchange parameters from overlapped signals of heme oxygenase-1, which is a relatively large protein. The results indicate that the structural flexibility of a kink in the heme-binding site is important for efficient heme binding. Relaxation dispersion difference requires neither selectively labeled samples nor modification of pulse programs; thus it will have wide applications in protein dynamics analysis.

Single-cell analyses reveal that KISS1R-expressing cells undergo sustained kisspeptin-induced signaling that is dependent upon an influx of extracellular Ca2+.

PubMed

Babwah, Andy V; Pampillo, Macarena; Min, Le; Kaiser, Ursula B; Bhattacharya, Moshmi

2012-12-01

The kisspeptin receptor (KISS1R) is a Gα(q/11)-coupled seven-transmembrane receptor activated by a group of peptides referred to as kisspeptins (Kps). The Kp/KISS1R signaling system is a powerful regulator of GnRH secretion, and inactivating mutations in this system are associated with hypogonadotropic hypogonadism. A recent study revealed that Kp triggers prolonged signaling; not from the inability of the receptor to undergo rapid desensitization, but instead from the maintenance of a dynamic and active pool of KISS1R at the cell surface. To investigate this further, we hypothesized that if a dynamic pool of receptor is maintained at the cell surface for a protracted period, chronic Kp-10 treatment would trigger the sustained activation of Gα(q/11) as evidenced through the prolonged activation of phospholipase C, protein kinase C, and prolonged mobilization of intracellular Ca(2+). Through single-cell analyses, we tested our hypothesis in human embryonic kidney (HEK) 293 cells and found that was indeed the case. We subsequently determined that prolonged KISS1R signaling was not a phenomenon specific to HEK 293 cells but is likely a conserved property of KISS1R-expressing cells because evidence of sustained KISS1R signaling was also observed in the GT1-7 GnRH neuronal and Chinese hamster ovary cell lines. While exploring the regulation of prolonged KISS1R signaling, we identified a critical role for extracellular Ca(2+). We found that although free intracellular Ca(2+), primarily derived from intracellular stores, was sufficient to trigger the acute activation of a major KISS1R secondary effector, protein kinase C, it was insufficient to sustain chronic KISS1R signaling; instead extracellular Ca(2+) was absolutely required for this.

Dynamic NF-κB and E2F interactions control the priority and timing of inflammatory signalling and cell proliferation

PubMed Central

Ankers, John M; Awais, Raheela; Jones, Nicholas A; Boyd, James; Ryan, Sheila; Adamson, Antony D; Harper, Claire V; Bridge, Lloyd; Spiller, David G; Jackson, Dean A; Paszek, Pawel; Sée, Violaine; White, Michael RH

2016-01-01

Dynamic cellular systems reprogram gene expression to ensure appropriate cellular fate responses to specific extracellular cues. Here we demonstrate that the dynamics of Nuclear Factor kappa B (NF-κB) signalling and the cell cycle are prioritised differently depending on the timing of an inflammatory signal. Using iterative experimental and computational analyses, we show physical and functional interactions between NF-κB and the E2 Factor 1 (E2F-1) and E2 Factor 4 (E2F-4) cell cycle regulators. These interactions modulate the NF-κB response. In S-phase, the NF-κB response was delayed or repressed, while cell cycle progression was unimpeded. By contrast, activation of NF-κB at the G1/S boundary resulted in a longer cell cycle and more synchronous initial NF-κB responses between cells. These data identify new mechanisms by which the cellular response to stress is differentially controlled at different stages of the cell cycle. DOI: http://dx.doi.org/10.7554/eLife.10473.001 PMID:27185527

The dynamics of color signals in male threespine sticklebacks Gasterosteus aculeatus

PubMed Central

Hiermes, Meike

2016-01-01

Abstract Body coloration and color patterns are ubiquitous throughout the animal kingdom and vary between and within species. Recent studies have dealt with individual dynamics of various aspects of coloration, as it is in many cases a flexible trait and changes in color expression may be context-dependent. During the reproductive phase, temporal changes of coloration in the visible spectral range (400–700 nm) have been shown for many animals but corresponding changes in the ultraviolet (UV) waveband (300–400 nm) have rarely been studied. Threespine stickleback Gasterosteus aculeatus males develop conspicuous orange–red breeding coloration combined with UV reflectance in the cheek region. We investigated dynamics of color patterns including UV throughout a male breeding cycle, as well as short-term changes in coloration in response to a computer-animated rival using reflectance spectrophotometry and visual modeling, to estimate how colors would be perceived by conspecifics. We found the orange–red component of coloration to vary during the breeding cycle with respect to hue (theta/R50) and intensity (achieved chroma/red chroma). Furthermore, color intensity in the orange–red spectral part (achieved chroma) tended to be increased after the presentation of an artificial rival. Dynamic changes in specific measures of hue and intensity in the UV waveband were not found. In general, the orange–red component of the signal seems to be dynamic with respect to color intensity and hue. This accounts in particular for color changes during the breeding cycle, presumably to signal reproductive status, and with limitations as well in the intrasexual context, most likely to signal dominance or inferiority. PMID:29491887

Signal enhancement in ligand-receptor interactions using dynamic polymers at quartz crystal microbalance sensors.

PubMed

Dunér, Gunnar; Anderson, Henrik; Pei, Zhichao; Ingemarsson, Björn; Aastrup, Teodor; Ramström, Olof

2016-06-20

The signal enhancement properties of QCM sensors based on dynamic, biotinylated poly(acrylic acid) brushes has been studied in interaction studies with an anti-biotin Fab fragment. The poly(acrylic acid) sensors showed a dramatic increase in signal response with more than ten times higher signal than the carboxyl-terminated self-assembled monolayer surface.

Performance Analysis of Control Signal Transmission Technique for Cognitive Radios in Dynamic Spectrum Access Networks

NASA Astrophysics Data System (ADS)

Sakata, Ren; Tomioka, Tazuko; Kobayashi, Takahiro

When cognitive radio (CR) systems dynamically use the frequency band, a control signal is necessary to indicate which carrier frequencies are currently available in the network. In order to keep efficient spectrum utilization, this control signal also should be transmitted based on the channel conditions. If transmitters dynamically select carrier frequencies, receivers have to receive control signals without knowledge of their carrier frequencies. To enable such transmission and reception, this paper proposes a novel scheme called DCPT (Differential Code Parallel Transmission). With DCPT, receivers can receive low-rate information with no knowledge of the carrier frequencies. The transmitter transmits two signals whose carrier frequencies are spaced by a predefined value. The absolute values of the carrier frequencies can be varied. When the receiver acquires the DCPT signal, it multiplies the signal by a frequency-shifted version of the signal; this yields a DC component that represents the data signal which is then demodulated. The performance was evaluated by means of numerical analysis and computer simulation. We confirmed that DCPT operates successfully even under severe interference if its parameters are appropriately configured.

Post-Correlation Semi-Coherent Integration for High-Dynamic and Weak GPS Signal Acquisition (Preprint)

DTIC Science & Technology

2008-06-01

provide the coverage. To enable weak GPS signal acquisition , one known technique at the receiver end is to extend the signal integration time...Han, “Block Accumulating Coherent Integration Over Extended Interval (BACIX) for Weak GPS Signal Acquisition ,” Proc. of ION-GNSS’06, Ft. Worth, TX...AFRL-RY-WP-TP-2008-1158 POST-CORRELATION SEMI-COHERENT INTEGRATION FOR HIGH-DYNAMIC AND WEAK GPS SIGNAL ACQUISITION (PREPRINT) Chun Yang

Regulation of branching dynamics by axon-intrinsic asymmetries in Tyrosine Kinase Receptor signaling

PubMed Central

Zschätzsch, Marlen; Oliva, Carlos; Langen, Marion; De Geest, Natalie; Özel, Mehmet Neset; Williamson, W Ryan; Lemon, William C; Soldano, Alessia; Munck, Sebastian; Hiesinger, P Robin; Sanchez-Soriano, Natalia; Hassan, Bassem A

2014-01-01

Axonal branching allows a neuron to connect to several targets, increasing neuronal circuit complexity. While axonal branching is well described, the mechanisms that control it remain largely unknown. We find that in the Drosophila CNS branches develop through a process of excessive growth followed by pruning. In vivo high-resolution live imaging of developing brains as well as loss and gain of function experiments show that activation of Epidermal Growth Factor Receptor (EGFR) is necessary for branch dynamics and the final branching pattern. Live imaging also reveals that intrinsic asymmetry in EGFR localization regulates the balance between dynamic and static filopodia. Elimination of signaling asymmetry by either loss or gain of EGFR function results in reduced dynamics leading to excessive branch formation. In summary, we propose that the dynamic process of axon branch development is mediated by differential local distribution of signaling receptors. DOI: http://dx.doi.org/10.7554/eLife.01699.001 PMID:24755286

Dynamic eye colour as an honest signal of aggression.

PubMed

Heathcote, Robert J P; Darden, Safi K; Troscianko, Jolyon; Lawson, Michael R M; Brown, Antony M; Laker, Philippa R; Naisbett-Jones, Lewis C; MacGregor, Hannah E A; Ramnarine, Indar; Croft, Darren P

2018-06-04

Animal eyes are some of the most widely recognisable structures in nature. Due to their salience to predators and prey, most research has focused on how animals hide or camouflage their eyes [1]. However, across all vertebrate Classes, many species actually express brightly coloured or conspicuous eyes, suggesting they may have also evolved a signalling function. Nevertheless, perhaps due to the difficulty with experimentally manipulating eye appearance, very few species beyond humans [2] have been experimentally shown to use eyes as signals [3]. Using staged behavioural trials we show that Trinidadian guppies (Poecilia reticulata), which can rapidly change their iris colour, predominantly express conspicuous eye colouration when performing aggressive behaviours towards smaller conspecifics. Furthermore, using a novel, visually realistic robotic system to create a mismatch between signal and relative competitive ability, we show that eye colour is used to honestly signal aggressive motivation. Specifically, robotic 'cheats' (that is, smaller, less-competitive robotic fish that display aggressive eye colouration when defending a food patch) attracted greater food competition from larger real fish. Our study suggests that eye colour may be an under-appreciated aspect of signalling in animals, shows the utility of our biomimetic robotic system for investigating animal behaviour, and provides experimental evidence that socially mediated costs towards low-quality individuals may maintain the honesty of dynamic colour signals. Copyright © 2018 Elsevier Ltd. All rights reserved.

Digital signal processing for velocity measurements in dynamical material's behaviour studies.

PubMed

Devlaminck, Julien; Luc, Jérôme; Chanal, Pierre-Yves

2014-03-01

In this work, we describe different configurations of optical fiber interferometers (types Michelson and Mach-Zehnder) used to measure velocities during dynamical material's behaviour studies. We detail the algorithms of processing developed and optimized to improve the performance of these interferometers especially in terms of time and frequency resolutions. Three methods of analysis of interferometric signals were studied. For Michelson interferometers, the time-frequency analysis of signals by Short-Time Fourier Transform (STFT) is compared to a time-frequency analysis by Continuous Wavelet Transform (CWT). The results have shown that the CWT was more suitable than the STFT for signals with low signal-to-noise, and low velocity and high acceleration areas. For Mach-Zehnder interferometers, the measurement is carried out by analyzing the phase shift between three interferometric signals (Triature processing). These three methods of digital signal processing were evaluated, their measurement uncertainties estimated, and their restrictions or operational limitations specified from experimental results performed on a pulsed power machine.

Cellular context–mediated Akt dynamics regulates MAP kinase signaling thresholds during angiogenesis

PubMed Central

Hellesøy, Monica; Lorens, James B.

2015-01-01

The formation of new blood vessels by sprouting angiogenesis is tightly regulated by contextual cues that affect angiogeneic growth factor signaling. Both constitutive activation and loss of Akt kinase activity in endothelial cells impair angiogenesis, suggesting that Akt dynamics mediates contextual microenvironmental regulation. We explored the temporal regulation of Akt in endothelial cells during formation of capillary-like networks induced by cell–cell contact with vascular smooth muscle cells (vSMCs) and vSMC-associated VEGF. Expression of constitutively active Akt1 strongly inhibited network formation, whereas hemiphosphorylated Akt1 epi-alleles with reduced kinase activity had an intermediate inhibitory effect. Conversely, inhibition of Akt signaling did not affect endothelial cell migration or morphogenesis in vSMC cocultures that generate capillary-like structures. We found that endothelial Akt activity is transiently blocked by proteasomal degradation in the presence of SMCs during the initial phase of capillary-like structure formation. Suppressed Akt activity corresponded to the increased endothelial MAP kinase signaling that was required for angiogenic endothelial morphogenesis. These results reveal a regulatory principle by which cellular context regulates Akt protein dynamics, which determines MAP kinase signaling thresholds necessary drive a morphogenetic program during angiogenesis. PMID:26023089

Dynamic Target Match Signals in Perirhinal Cortex Can Be Explained by Instantaneous Computations That Act on Dynamic Input from Inferotemporal Cortex

PubMed Central

Pagan, Marino

2014-01-01

Finding sought objects requires the brain to combine visual and target signals to determine when a target is in view. To investigate how the brain implements these computations, we recorded neural responses in inferotemporal cortex (IT) and perirhinal cortex (PRH) as macaque monkeys performed a delayed-match-to-sample target search task. Our data suggest that visual and target signals were combined within or before IT in the ventral visual pathway and then passed onto PRH, where they were reformatted into a more explicit target match signal over ∼10–15 ms. Accounting for these dynamics in PRH did not require proposing dynamic computations within PRH itself but, rather, could be attributed to instantaneous PRH computations performed upon an input representation from IT that changed with time. We found that the dynamics of the IT representation arose from two commonly observed features: individual IT neurons whose response preferences were not simply rescaled with time and variable response latencies across the population. Our results demonstrate that these types of time-varying responses have important consequences for downstream computation and suggest that dynamic representations can arise within a feedforward framework as a consequence of instantaneous computations performed upon time-varying inputs. PMID:25122904

Dynamics of the actin cytoskeleton mediates receptor cross talk: An emerging concept in tuning receptor signaling

PubMed Central

Mattila, Pieta K.; Batista, Facundo D.

2016-01-01

Recent evidence implicates the actin cytoskeleton in the control of receptor signaling. This may be of particular importance in the context of immune receptors, such as the B cell receptor, where dysregulated signaling can result in autoimmunity and malignancy. Here, we discuss the role of the actin cytoskeleton in controlling receptor compartmentalization, dynamics, and clustering as a means to regulate receptor signaling through controlling the interactions with protein partners. We propose that the actin cytoskeleton is a point of integration for receptor cross talk through modulation of protein dynamics and clustering. We discuss the implication of this cross talk via the cytoskeleton for both ligand-induced and low-level constitutive (tonic) signaling necessary for immune cell survival. PMID:26833785

MRI dynamic range and its compatibility with signal transmission media

PubMed Central

Gabr, Refaat E.; Schär, Michael; Edelstein, Arthur D.; Kraitchman, Dara L.; Bottomley, Paul A.; Edelstein, William A.

2010-01-01

As the number of MRI phased array coil elements grows, interactions among cables connecting them to the system receiver become increasingly problematic. Fiber optic or wireless links would reduce electromagnetic interference, but their dynamic range (DR) is generally less than that of coaxial cables. Raw MRI signals, however, have a large DR because of the high signal amplitude near the center of k-space. Here, we study DR in MRI in order to determine the compatibility of MRI multicoil imaging with non-coaxial cable signal transmission. Since raw signal data are routinely discarded, we have developed an improved method for estimating the DR of MRI signals from conventional magnitude images. Our results indicate that the DR of typical surface coil signals at 3 T for human subjects is less than 88 dB, even for three-dimensional acquisition protocols. Cardiac and spine coil arrays had a maximum DR of less than 75 dB and head coil arrays less than 88 dB. The DR derived from magnitude images is in good agreement with that measured from raw data. The results suggest that current analog fiber optic links, with a spurious-free DR of 60–70 dB at 500 kHz bandwidth, are not by themselves adequate for transmitting MRI data from volume or array coils with DR ~90 dB. However, combining analog links with signal compression might make non-coaxial cable signal transmission viable. PMID:19251444

MRI dynamic range and its compatibility with signal transmission media.

PubMed

Gabr, Refaat E; Schär, Michael; Edelstein, Arthur D; Kraitchman, Dara L; Bottomley, Paul A; Edelstein, William A

2009-06-01

As the number of MRI phased array coil elements grows, interactions among cables connecting them to the system receiver become increasingly problematic. Fiber optic or wireless links would reduce electromagnetic interference, but their dynamic range (DR) is generally less than that of coaxial cables. Raw MRI signals, however, have a large DR because of the high signal amplitude near the center of k-space. Here, we study DR in MRI in order to determine the compatibility of MRI multicoil imaging with non-coaxial cable signal transmission. Since raw signal data are routinely discarded, we have developed an improved method for estimating the DR of MRI signals from conventional magnitude images. Our results indicate that the DR of typical surface coil signals at 3T for human subjects is less than 88 dB, even for three-dimensional acquisition protocols. Cardiac and spine coil arrays had a maximum DR of less than 75 dB and head coil arrays less than 88 dB. The DR derived from magnitude images is in good agreement with that measured from raw data. The results suggest that current analog fiber optic links, with a spurious-free DR of 60-70 dB at 500 kHz bandwidth, are not by themselves adequate for transmitting MRI data from volume or array coils with DR approximately 90 dB. However, combining analog links with signal compression might make non-coaxial cable signal transmission viable.

Comparative survey of dynamic analyses of free-piston Stirling engines

NASA Technical Reports Server (NTRS)

Kankam, M. D.; Rauch, J. S.

1991-01-01

Reported dynamics analyses for evaluating the steady-state response and stability of free-piston Stirling engine (FPSE) systems are compared. Various analytical approaches are discussed to provide guidance on their salient features. Recommendations are made in the recommendations remarks for an approach which captures most of the inherent properties of the engine. Such an approach has the potential for yielding results which will closely match practical FPSE-load systems.

Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants.

PubMed

Varala, Kranthi; Marshall-Colón, Amy; Cirrone, Jacopo; Brooks, Matthew D; Pasquino, Angelo V; Léran, Sophie; Mittal, Shipra; Rock, Tara M; Edwards, Molly B; Kim, Grace J; Ruffel, Sandrine; McCombie, W Richard; Shasha, Dennis; Coruzzi, Gloria M

2018-06-19

This study exploits time, the relatively unexplored fourth dimension of gene regulatory networks (GRNs), to learn the temporal transcriptional logic underlying dynamic nitrogen (N) signaling in plants. Our "just-in-time" analysis of time-series transcriptome data uncovered a temporal cascade of cis elements underlying dynamic N signaling. To infer transcription factor (TF)-target edges in a GRN, we applied a time-based machine learning method to 2,174 dynamic N-responsive genes. We experimentally determined a network precision cutoff, using TF-regulated genome-wide targets of three TF hubs (CRF4, SNZ, and CDF1), used to "prune" the network to 155 TFs and 608 targets. This network precision was reconfirmed using genome-wide TF-target regulation data for four additional TFs (TGA1, HHO5/6, and PHL1) not used in network pruning. These higher-confidence edges in the GRN were further filtered by independent TF-target binding data, used to calculate a TF "N-specificity" index. This refined GRN identifies the temporal relationship of known/validated regulators of N signaling (NLP7/8, TGA1/4, NAC4, HRS1, and LBD37/38/39) and 146 additional regulators. Six TFs-CRF4, SNZ, CDF1, HHO5/6, and PHL1-validated herein regulate a significant number of genes in the dynamic N response, targeting 54% of N-uptake/assimilation pathway genes. Phenotypically, inducible overexpression of CRF4 in planta regulates genes resulting in altered biomass, root development, and 15 NO 3 - uptake, specifically under low-N conditions. This dynamic N-signaling GRN now provides the temporal "transcriptional logic" for 155 candidate TFs to improve nitrogen use efficiency with potential agricultural applications. Broadly, these time-based approaches can uncover the temporal transcriptional logic for any biological response system in biology, agriculture, or medicine. Copyright © 2018 the Author(s). Published by PNAS.

Inverting dynamic force microscopy: From signals to time-resolved interaction forces

PubMed Central

Stark, Martin; Stark, Robert W.; Heckl, Wolfgang M.; Guckenberger, Reinhard

2002-01-01

Transient forces between nanoscale objects on surfaces govern friction, viscous flow, and plastic deformation, occur during manipulation of matter, or mediate the local wetting behavior of thin films. To resolve transient forces on the (sub) microsecond time and nanometer length scale, dynamic atomic force microscopy (AFM) offers largely unexploited potential. Full spectral analysis of the AFM signal completes dynamic AFM. Inverting the signal formation process, we measure the time course of the force effective at the sensing tip. This approach yields rich insight into processes at the tip and dispenses with a priori assumptions about the interaction, as it relies solely on measured data. Force measurements on silicon under ambient conditions demonstrate the distinct signature of the interaction and reveal that peak forces exceeding 200 nN are applied to the sample in a typical imaging situation. These forces are 2 orders of magnitude higher than those in covalent bonds. PMID:12070341

Dynamic Range Enhancement of High-Speed Electrical Signal Data via Non-Linear Compression

NASA Technical Reports Server (NTRS)

Laun, Matthew C. (Inventor)

2016-01-01

Systems and methods for high-speed compression of dynamic electrical signal waveforms to extend the measuring capabilities of conventional measuring devices such as oscilloscopes and high-speed data acquisition systems are discussed. Transfer function components and algorithmic transfer functions can be used to accurately measure signals that are within the frequency bandwidth but beyond the voltage range and voltage resolution capabilities of the measuring device.

Stat5 Signaling Specifies Basal versus Stress Erythropoietic Responses through Distinct Binary and Graded Dynamic Modalities

PubMed Central

Porpiglia, Ermelinda; Hidalgo, Daniel; Koulnis, Miroslav; Tzafriri, Abraham R.; Socolovsky, Merav

2012-01-01

Erythropoietin (Epo)-induced Stat5 phosphorylation (p-Stat5) is essential for both basal erythropoiesis and for its acceleration during hypoxic stress. A key challenge lies in understanding how Stat5 signaling elicits distinct functions during basal and stress erythropoiesis. Here we asked whether these distinct functions might be specified by the dynamic behavior of the Stat5 signal. We used flow cytometry to analyze Stat5 phosphorylation dynamics in primary erythropoietic tissue in vivo and in vitro, identifying two signaling modalities. In later (basophilic) erythroblasts, Epo stimulation triggers a low intensity but decisive, binary (digital) p-Stat5 signal. In early erythroblasts the binary signal is superseded by a high-intensity graded (analog) p-Stat5 response. We elucidated the biological functions of binary and graded Stat5 signaling using the EpoR-HM mice, which express a “knocked-in” EpoR mutant lacking cytoplasmic phosphotyrosines. Strikingly, EpoR-HM mice are restricted to the binary signaling mode, which rescues these mice from fatal perinatal anemia by promoting binary survival decisions in erythroblasts. However, the absence of the graded p-Stat5 response in the EpoR-HM mice prevents them from accelerating red cell production in response to stress, including a failure to upregulate the transferrin receptor, which we show is a novel stress target. We found that Stat5 protein levels decline with erythroblast differentiation, governing the transition from high-intensity graded signaling in early erythroblasts to low-intensity binary signaling in later erythroblasts. Thus, using exogenous Stat5, we converted later erythroblasts into high-intensity graded signal transducers capable of eliciting a downstream stress response. Unlike the Stat5 protein, EpoR expression in erythroblasts does not limit the Stat5 signaling response, a non-Michaelian paradigm with therapeutic implications in myeloproliferative disease. Our findings show how the binary and

Novel method of using dynamic electrical impedance signals for noninvasive diagnosis of knee osteoarthritis.

PubMed

Gajre, Suhas S; Anand, Sneh; Singh, U; Saxena, Rajendra K

2006-01-01

Osteoarthritis (OA) of knee is the most commonly occurring non-fatal irreversible disease, mainly in the elderly population and particularly in female. Various invasive and non-invasive methods are reported for the diagnosis of this articular cartilage pathology. Well known techniques such as X-ray, computed tomography, magnetic resonance imaging, arthroscopy and arthrography are having their disadvantages, and diagnosis of OA in early stages with simple effective noninvasive method is still a biomedical engineering problem. Analyzing knee joint noninvasive signals around knee might give simple solution for diagnosis of knee OA. We used electrical impedance data from knees to compare normal and osteoarthritic subjects during the most common dynamic conditions of the knee, i.e. walking and knee swing. It was found that there is substantial difference in the properties of the walking cycle (WC) and knee swing cycle (KS) signals. In experiments on 90 pathological (combined for KS and WC signals) and 72 normal signals (combined), suitable features were drawn. Then signals were used to classify as normal or pathological. Artificial multilayer feed forward neural network was trained using back propagation algorithm for the classification. On a training data set of 54 signals for KS signals, the classification efficiency for a test set of 54 was 70.37% and 85.19% with and without normalization respectively wrt base impedance. Similarly, the training set of 27 WC signals and test set of 27 signals resulted in 77.78% and 66.67% classification efficiency. The results indicate that dynamic electrical impedance signals have potential to be used as a novel method for noninvasive diagnosis of knee OA.

Competitive aggregation dynamics using phase wave signals.

PubMed

Sakaguchi, Hidetsugu; Maeyama, Satomi

2014-10-21

Coupled equations of the phase equation and the equation of cell concentration n are proposed for competitive aggregation dynamics of slime mold in two dimensions. Phase waves are used as tactic signals of aggregation in this model. Several aggregation clusters are formed initially, and target patterns appear around the localized aggregation clusters. Owing to the competition among target patterns, the number of the localized aggregation clusters decreases, and finally one dominant localized pattern survives. If the phase equation is replaced with the complex Ginzburg-Landau equation, several spiral patterns appear, and n is localized near the center of the spiral patterns. After the competition among spiral patterns, one dominant spiral survives. Copyright © 2014 Elsevier Ltd. All rights reserved.

Global navigation satellite system receiver for weak signals under all dynamic conditions

NASA Astrophysics Data System (ADS)

Ziedan, Nesreen Ibrahim

The ability of the Global Navigation Satellite System (GNSS) receiver to work under weak signal and various dynamic conditions is required in some applications. For example, to provide a positioning capability in wireless devices, or orbit determination of Geostationary and high Earth orbit satellites. This dissertation develops Global Positioning System (GPS) receiver algorithms for such applications. Fifteen algorithms are developed for the GPS C/A signal. They cover all the receiver main functions, which include acquisition, fine acquisition, bit synchronization, code and carrier tracking, and navigation message decoding. They are integrated together, and they can be used in any software GPS receiver. They also can be modified to fit any other GPS or GNSS signals. The algorithms have new capabilities. The processing and memory requirements are considered in the design to allow the algorithms to fit the limited resources of some applications; they do not require any assisting information. Weak signals can be acquired in the presence of strong interfering signals and under high dynamic conditions. The fine acquisition, bit synchronization, and tracking algorithms are based on the Viterbi algorithm and Extended Kalman filter approaches. The tracking algorithms capabilities increase the time to lose lock. They have the ability to adaptively change the integration length and the code delay separation. More than one code delay separation can be used in the same time. Large tracking errors can be detected and then corrected by a re-initialization and an acquisition-like algorithms. Detecting the navigation message is needed to increase the coherent integration; decoding it is needed to calculate the navigation solution. The decoding algorithm utilizes the message structure to enable its decoding for signals with high Bit Error Rate. The algorithms are demonstrated using simulated GPS C/A code signals, and TCXO clocks. The results have shown the algorithms ability to

Seasonal dynamics of VLF signals amplitude Novosibirsk radio station and mesopause region temperature in 2009-2015

NASA Astrophysics Data System (ADS)

Kozlov, V. I.; Korsakov, A. A.; Ammosov, P. P.; Ammosova, A. M.; Gavrilyeva, G. A.; Koltovskoi, I. I.

2017-11-01

Dynamics of seasonal variations in the amplitude of the VLF radio signal received in Yakutsk from the navigation station near Novosibirsk and the radiation intensity in the wavelength range from 835 to 853 nm, where the P-branches of the OH band (6-2) are located, is present. The radiation variations give information about mesopause region measured at the Maimaga station (130 km from Yakutsk). Observation period from 2009 to 2015 covers period with minimum and maximum solar activity (solar flux F10.7). In the seasonal dynamics of the VLF amplitude signals and the mesopause temperature are observed annual, semiannual and third-annual variations, increasing during nighttime for VLF signals. The mesopause temperature and the VLF signal increase with increasing solar flux F10.7 in winter.

Bioreactors to Influence Stem Cell Fate: Augmentation of Mesenchymal Stem Cell Signaling Pathways via Dynamic Culture Systems

PubMed Central

Yeatts, Andrew B.; Choquette, Daniel T.; Fisher, John P.

2012-01-01

Background Mesenchymal stem cells (MSCs) are a promising cell source for bone and cartilage tissue engineering as they can be easily isolated from the body and differentiated into osteoblasts and chondrocytes. A cell based tissue engineering strategy using MSCs often involves the culture of these cells on three-dimensional scaffolds; however the size of these scaffolds and the cell population they can support can be restricted in traditional static culture. Thus dynamic culture in bioreactor systems provides a promising means to culture and differentiate MSCs in vitro. Scope of Review This review seeks to characterize key MSC differentiation signaling pathways and provides evidence as to how dynamic culture is augmenting these pathways. Following an overview of dynamic culture systems, discussion will be provided on how these systems can effectively modify and maintain important culture parameters including oxygen content and shear stress. Literature is reviewed for both a highlight of key signaling pathways and evidence for regulation of these signaling pathways via dynamic culture systems. Major Conclusions The ability to understand how these culture systems are affecting MSC signaling pathways could lead to a shear or oxygen regime to direct stem cell differentiation. In this way the efficacy of in vitro culture and differentiation of MSCs on three-dimensional scaffolds could be greatly increased. General Significance Bioreactor systems have the ability to control many key differentiation stimuli including mechanical stress and oxygen content. The further integration of cell signaling investigations within dynamic culture systems will lead to a quicker realization of the promise of tissue engineering and regenerative medicine. PMID:22705676

Enhanced resting-state dynamics of the hemoglobin signal as a novel biomarker for detection of breast cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graber, Harry L., E-mail: harry.graber@downstate.edu; Xu, Yong; Barbour, Randall L.

Purpose: The work presented here demonstrates an application of diffuse optical tomography (DOT) to the problem of breast-cancer diagnosis. The potential for using spatial and temporal variability measures of the hemoglobin signal to identify useful biomarkers was studied. Methods: DOT imaging data were collected using two instrumentation platforms the authors developed, which were suitable for exploring tissue dynamics while performing a simultaneous bilateral exam. For each component of the hemoglobin signal (e.g., total, oxygenated), the image time series was reduced to eight scalar metrics that were affected by one or more dynamic properties of the breast microvasculature (e.g., average amplitude,more » amplitude heterogeneity, strength of spatial coordination). Receiver-operator characteristic (ROC) analyses, comparing groups of subjects with breast cancer to various control groups (i.e., all noncancer subjects, only those with diagnosed benign breast pathology, and only those with no known breast pathology), were performed to evaluate the effect of cancer on the magnitudes of the metrics and of their interbreast differences and ratios. Results: For women with known breast cancer, simultaneous bilateral DOT breast measures reveal a marked increase in the resting-state amplitude of the vasomotor response in the hemoglobin signal for the affected breast, compared to the contralateral, noncancer breast. Reconstructed 3D spatial maps of observed dynamics also show that this behavior extends well beyond the tumor border. In an effort to identify biomarkers that have the potential to support clinical aims, a group of scalar quantities extracted from the time series measures was systematically examined. This analysis showed that many of the quantities obtained by computing paired responses from the bilateral scans (e.g., interbreast differences, ratios) reveal statistically significant differences between the cancer-positive and -negative subject groups, while the

Responses to auxin signals: an operating principle for dynamical sensitivity yet high resilience

PubMed Central

Bravi, B.; Martin, O. C.

2018-01-01

Plants depend on the signalling of the phytohormone auxin for their development and for responding to environmental perturbations. The associated biomolecular signalling network involves a negative feedback on Aux/IAA proteins which mediate the influence of auxin (the signal) on the auxin response factor (ARF) transcription factors (the drivers of the response). To probe the role of this feedback, we consider alternative in silico signalling networks implementing different operating principles. By a comparative analysis, we find that the presence of a negative feedback allows the system to have a far larger sensitivity in its dynamical response to auxin and that this sensitivity does not prevent the system from being highly resilient. Given this insight, we build a new biomolecular signalling model for quantitatively describing such Aux/IAA and ARF responses. PMID:29410878

Sig2GRN: a software tool linking signaling pathway with gene regulatory network for dynamic simulation.

PubMed

Zhang, Fan; Liu, Runsheng; Zheng, Jie

2016-12-23

Linking computational models of signaling pathways to predicted cellular responses such as gene expression regulation is a major challenge in computational systems biology. In this work, we present Sig2GRN, a Cytoscape plugin that is able to simulate time-course gene expression data given the user-defined external stimuli to the signaling pathways. A generalized logical model is used in modeling the upstream signaling pathways. Then a Boolean model and a thermodynamics-based model are employed to predict the downstream changes in gene expression based on the simulated dynamics of transcription factors in signaling pathways. Our empirical case studies show that the simulation of Sig2GRN can predict changes in gene expression patterns induced by DNA damage signals and drug treatments. As a software tool for modeling cellular dynamics, Sig2GRN can facilitate studies in systems biology by hypotheses generation and wet-lab experimental design. http://histone.scse.ntu.edu.sg/Sig2GRN/.

Discrete Dynamics Model for the Speract-Activated Ca2+ Signaling Network Relevant to Sperm Motility

PubMed Central

Espinal, Jesús; Aldana, Maximino; Guerrero, Adán; Wood, Christopher

2011-01-01

Understanding how spermatozoa approach the egg is a central biological issue. Recently a considerable amount of experimental evidence has accumulated on the relation between oscillations in intracellular calcium ion concentration ([Ca]) in the sea urchin sperm flagellum, triggered by peptides secreted from the egg, and sperm motility. Determination of the structure and dynamics of the signaling pathway leading to these oscillations is a fundamental problem. However, a biochemically based formulation for the comprehension of the molecular mechanisms operating in the axoneme as a response to external stimulus is still lacking. Based on experiments on the S. purpuratus sea urchin spermatozoa, we propose a signaling network model where nodes are discrete variables corresponding to the pathway elements and the signal transmission takes place at discrete time intervals according to logical rules. The validity of this model is corroborated by reproducing previous empirically determined signaling features. Prompted by the model predictions we performed experiments which identified novel characteristics of the signaling pathway. We uncovered the role of a high voltage-activated channel as a regulator of the delay in the onset of fluctuations after activation of the signaling cascade. This delay time has recently been shown to be an important regulatory factor for sea urchin sperm reorientation. Another finding is the participation of a voltage-dependent calcium-activated channel in the determination of the period of the fluctuations. Furthermore, by analyzing the spread of network perturbations we find that it operates in a dynamically critical regime. Our work demonstrates that a coarse-grained approach to the dynamics of the signaling pathway is capable of revealing regulatory sperm navigation elements and provides insight, in terms of criticality, on the concurrence of the high robustness and adaptability that the reproduction processes are predicted to have developed

Extracting a respiratory signal from raw dynamic PET data that contain tracer kinetics.

PubMed

Schleyer, P J; Thielemans, K; Marsden, P K

2014-08-07

Data driven gating (DDG) methods provide an alternative to hardware based respiratory gating for PET imaging. Several existing DDG approaches obtain a respiratory signal by observing the change in PET-counts within specific regions of acquired PET data. Currently, these methods do not allow for tracer kinetics which can interfere with the respiratory signal and introduce error. In this work, we produced a DDG method for dynamic PET studies that exhibit tracer kinetics. Our method is based on an existing approach that uses frequency-domain analysis to locate regions within raw PET data that are subject to respiratory motion. In the new approach, an optimised non-stationary short-time Fourier transform was used to create a time-varying 4D map of motion affected regions. Additional processing was required to ensure that the relationship between the sign of the respiratory signal and the physical direction of movement remained consistent for each temporal segment of the 4D map. The change in PET-counts within the 4D map during the PET acquisition was then used to generate a respiratory curve. Using 26 min dynamic cardiac NH3 PET acquisitions which included a hardware derived respiratory measurement, we show that tracer kinetics can severely degrade the respiratory signal generated by the original DDG method. In some cases, the transition of tracer from the liver to the lungs caused the respiratory signal to invert. The new approach successfully compensated for tracer kinetics and improved the correlation between the data-driven and hardware based signals. On average, good correlation was maintained throughout the PET acquisitions.

A digital-signal-processor-based optical tomographic system for dynamic imaging of joint diseases

NASA Astrophysics Data System (ADS)

Lasker, Joseph M.

Over the last decade, optical tomography (OT) has emerged as viable biomedical imaging modality. Various imaging systems have been developed that are employed in preclinical as well as clinical studies, mostly targeting breast imaging, brain imaging, and cancer related studies. Of particular interest are so-called dynamic imaging studies where one attempts to image changes in optical properties and/or physiological parameters as they occur during a system perturbation. To successfully perform dynamic imaging studies, great effort is put towards system development that offers increasingly enhanced signal-to-noise performance at ever shorter data acquisition times, thus capturing high fidelity tomographic data within narrower time periods. Towards this goal, I have developed in this thesis a dynamic optical tomography system that is, unlike currently available analog instrumentation, based on digital data acquisition and filtering techniques. At the core of this instrument is a digital signal processor (DSP) that collects, collates, and processes the digitized data set. Complementary protocols between the DSP and a complex programmable logic device synchronizes the sampling process and organizes data flow. Instrument control is implemented through a comprehensive graphical user interface which integrates automated calibration, data acquisition, and signal post-processing. Real-time data is generated at frame rates as high as 140 Hz. An extensive dynamic range (˜190 dB) accommodates a wide scope of measurement geometries and tissue types. Performance analysis demonstrates very low system noise (˜1 pW rms noise equivalent power), excellent signal precision (˜0.04%--0.2%) and long term system stability (˜1% over 40 min). Experiments on tissue phantoms validate spatial and temporal accuracy of the system. As a potential new application of dynamic optical imaging I present the first application of this method to use vascular hemodynamics as a means of characterizing

Dynamic time warping and machine learning for signal quality assessment of pulsatile signals.

PubMed

Li, Q; Clifford, G D

2012-09-01

In this work, we describe a beat-by-beat method for assessing the clinical utility of pulsatile waveforms, primarily recorded from cardiovascular blood volume or pressure changes, concentrating on the photoplethysmogram (PPG). Physiological blood flow is nonstationary, with pulses changing in height, width and morphology due to changes in heart rate, cardiac output, sensor type and hardware or software pre-processing requirements. Moreover, considerable inter-individual and sensor-location variability exists. Simple template matching methods are therefore inappropriate, and a patient-specific adaptive initialization is therefore required. We introduce dynamic time warping to stretch each beat to match a running template and combine it with several other features related to signal quality, including correlation and the percentage of the beat that appeared to be clipped. The features were then presented to a multi-layer perceptron neural network to learn the relationships between the parameters in the presence of good- and bad-quality pulses. An expert-labeled database of 1055 segments of PPG, each 6 s long, recorded from 104 separate critical care admissions during both normal and verified arrhythmic events, was used to train and test our algorithms. An accuracy of 97.5% on the training set and 95.2% on test set was found. The algorithm could be deployed as a stand-alone signal quality assessment algorithm for vetting the clinical utility of PPG traces or any similar quasi-periodic signal.

Dynamic crystallography reveals early signalling events in ultraviolet photoreceptor UVR8

DOE PAGES

Zeng, Xiaoli; Ren, Zhong; Wu, Qi; ...

2015-01-08

Arabidopsis thaliana UVR8 (AtUVR8) is a long-sought-after photoreceptor that undergoes dimer dissociation in response to UV-B light. Crystallographic and mutational studies have identified two crucial tryptophan residues for UV-B responses in AtUVR8. However, the mechanism of UV-B perception and structural events leading up to dimer dissociation remain elusive at the molecular level. We applied dynamic crystallography to capture light-induced structural events in photoactive AtUVR8 crystals. Here we report two intermediate structures at 1.67Å resolution. At the epicenter of UV-B signaling, concerted motions associated with Trp285/Trp233 lead to ejection of a water molecule, which weakens an intricate network of hydrogen bondsmore » and salt bridges at the dimer interface. Partial opening of the β-propeller structure due to thermal relaxation of conformational strains originating in the epicenter further disrupts the dimer interface and leads to dimer dissociation. Ultimately, these dynamic crystallographic observations provide structural insights into the photo-perception and signaling mechanism of UVR8.« less

Nonlinear Dynamic Characteristics of Oil-in-Water Emulsions

NASA Astrophysics Data System (ADS)

Yin, Zhaoqi; Han, Yunfeng; Ren, Yingyu; Yang, Qiuyi; Jin, Ningde

2016-08-01

In this article, the nonlinear dynamic characteristics of oil-in-water emulsions under the addition of surfactant were experimentally investigated. Firstly, based on the vertical upward oil-water two-phase flow experiment in 20 mm inner diameter (ID) testing pipe, dynamic response signals of oil-in-water emulsions were recorded using vertical multiple electrode array (VMEA) sensor. Afterwards, the recurrence plot (RP) algorithm and multi-scale weighted complexity entropy causality plane (MS-WCECP) were employed to analyse the nonlinear characteristics of the signals. The results show that the certainty is decreasing and the randomness is increasing with the increment of surfactant concentration. This article provides a novel method for revealing the nonlinear dynamic characteristics, complexity, and randomness of oil-in-water emulsions with experimental measurement signals.

MACF1 regulates the migration of pyramidal neurons via microtubule dynamics and GSK-3 signaling

PubMed Central

Ka, Minhan; Jung, Eui-Man; Mueller, Ulrich; Kim, Woo-Yang

2014-01-01

Neuronal migration and subsequent differentiation play critical roles for establishing functional neural circuitry in the developing brain. However, the molecular mechanisms that regulate these processes are poorly understood. Here, we show that microtubule actin crosslinking factor 1 (MACF1) determines neuronal positioning by regulating microtubule dynamics and mediating GSK-3 signaling during brain development. First, using MACF1 floxed allele mice and in utero gene manipulation, we find that MACF1 deletion suppresses migration of cortical pyramidal neurons and results in aberrant neuronal positioning in the developing brain. The cell autonomous deficit in migration is associated with abnormal dynamics of leading processes and centrosomes. Furthermore, microtubule stability is severely damaged in neurons lacking MACF1, resulting in abnormal microtubule dynamics. Finally, MACF1 interacts with and mediates GSK-3 signaling in developing neurons. Our findings establish a cellular mechanism underlying neuronal migration and provide insights into the regulation of cytoskeleton dynamics in developing neurons. PMID:25224226

MACF1 regulates the migration of pyramidal neurons via microtubule dynamics and GSK-3 signaling.

PubMed

Ka, Minhan; Jung, Eui-Man; Mueller, Ulrich; Kim, Woo-Yang

2014-11-01

Neuronal migration and subsequent differentiation play critical roles for establishing functional neural circuitry in the developing brain. However, the molecular mechanisms that regulate these processes are poorly understood. Here, we show that microtubule actin crosslinking factor 1 (MACF1) determines neuronal positioning by regulating microtubule dynamics and mediating GSK-3 signaling during brain development. First, using MACF1 floxed allele mice and in utero gene manipulation, we find that MACF1 deletion suppresses migration of cortical pyramidal neurons and results in aberrant neuronal positioning in the developing brain. The cell autonomous deficit in migration is associated with abnormal dynamics of leading processes and centrosomes. Furthermore, microtubule stability is severely damaged in neurons lacking MACF1, resulting in abnormal microtubule dynamics. Finally, MACF1 interacts with and mediates GSK-3 signaling in developing neurons. Our findings establish a cellular mechanism underlying neuronal migration and provide insights into the regulation of cytoskeleton dynamics in developing neurons. Copyright © 2014 Elsevier Inc. All rights reserved.

Dynamic Compression of the Signal in a Charge Sensitive Amplifier: From Concept to Design

NASA Astrophysics Data System (ADS)

Manghisoni, Massimo; Comotti, Daniele; Gaioni, Luigi; Ratti, Lodovico; Re, Valerio

2015-10-01

This work is concerned with the design of a low-noise Charge Sensitive Amplifier featuring a dynamic signal compression based on the non-linear features of an inversion-mode MOS capacitor. These features make the device suitable for applications where a non-linear characteristic of the front-end is required, such as in imaging instrumentation for free electron laser experiments. The aim of the paper is to discuss a methodology for the proper design of the feedback network enabling the dynamic signal compression. Starting from this compression solution, the design of a low-noise Charge Sensitive Amplifier is also discussed. The study has been carried out by referring to a 65 nm CMOS technology.

Identifying early-warning signals of critical transitions with strong noise by dynamical network markers

PubMed Central

Liu, Rui; Chen, Pei; Aihara, Kazuyuki; Chen, Luonan

2015-01-01

Identifying early-warning signals of a critical transition for a complex system is difficult, especially when the target system is constantly perturbed by big noise, which makes the traditional methods fail due to the strong fluctuations of the observed data. In this work, we show that the critical transition is not traditional state-transition but probability distribution-transition when the noise is not sufficiently small, which, however, is a ubiquitous case in real systems. We present a model-free computational method to detect the warning signals before such transitions. The key idea behind is a strategy: “making big noise smaller” by a distribution-embedding scheme, which transforms the data from the observed state-variables with big noise to their distribution-variables with small noise, and thus makes the traditional criteria effective because of the significantly reduced fluctuations. Specifically, increasing the dimension of the observed data by moment expansion that changes the system from state-dynamics to probability distribution-dynamics, we derive new data in a higher-dimensional space but with much smaller noise. Then, we develop a criterion based on the dynamical network marker (DNM) to signal the impending critical transition using the transformed higher-dimensional data. We also demonstrate the effectiveness of our method in biological, ecological and financial systems. PMID:26647650

Weak temporal signals can synchronize and accelerate the transition dynamics of biopolymers under tension.

PubMed

Kim, Won Kyu; Hyeon, Changbong; Sung, Wokyung

2012-09-04

In addition to thermal noise, which is essential to promote conformational transitions in biopolymers, the cellular environment is replete with a spectrum of athermal fluctuations that are produced from a plethora of active processes. To understand the effect of athermal noise on biological processes, we studied how a small oscillatory force affects the thermally induced folding and unfolding transition of an RNA hairpin, whose response to constant tension had been investigated extensively in both theory and experiments. Strikingly, our molecular simulations performed under overdamped condition show that even at a high (low) tension that renders the hairpin (un)folding improbable, a weak external oscillatory force at a certain frequency can synchronously enhance the transition dynamics of RNA hairpin and increase the mean transition rate. Furthermore, the RNA dynamics can still discriminate a signal with resonance frequency even when the signal is mixed among other signals with nonresonant frequencies. In fact, our computational demonstration of thermally induced resonance in RNA hairpin dynamics is a direct realization of the phenomena called stochastic resonance and resonant activation. Our study, amenable to experimental tests using optical tweezers, is of great significance to the folding of biopolymers in vivo that are subject to the broad spectrum of cellular noises.

Dynamic neural activity during stress signals resilient coping

PubMed Central

Sinha, Rajita; Lacadie, Cheryl M.; Constable, R. Todd; Seo, Dongju

2016-01-01

Active coping underlies a healthy stress response, but neural processes supporting such resilient coping are not well-known. Using a brief, sustained exposure paradigm contrasting highly stressful, threatening, and violent stimuli versus nonaversive neutral visual stimuli in a functional magnetic resonance imaging (fMRI) study, we show significant subjective, physiologic, and endocrine increases and temporally related dynamically distinct patterns of neural activation in brain circuits underlying the stress response. First, stress-specific sustained increases in the amygdala, striatum, hypothalamus, midbrain, right insula, and right dorsolateral prefrontal cortex (DLPFC) regions supported the stress processing and reactivity circuit. Second, dynamic neural activation during stress versus neutral runs, showing early increases followed by later reduced activation in the ventrolateral prefrontal cortex (VLPFC), dorsal anterior cingulate cortex (dACC), left DLPFC, hippocampus, and left insula, suggested a stress adaptation response network. Finally, dynamic stress-specific mobilization of the ventromedial prefrontal cortex (VmPFC), marked by initial hypoactivity followed by increased VmPFC activation, pointed to the VmPFC as a key locus of the emotional and behavioral control network. Consistent with this finding, greater neural flexibility signals in the VmPFC during stress correlated with active coping ratings whereas lower dynamic activity in the VmPFC also predicted a higher level of maladaptive coping behaviors in real life, including binge alcohol intake, emotional eating, and frequency of arguments and fights. These findings demonstrate acute functional neuroplasticity during stress, with distinct and separable brain networks that underlie critical components of the stress response, and a specific role for VmPFC neuroflexibility in stress-resilient coping. PMID:27432990

Weak and Dynamic GNSS Signal Tracking Strategies for Flight Missions in the Space Service Volume.

PubMed

Jing, Shuai; Zhan, Xingqun; Liu, Baoyu; Chen, Maolin

2016-09-02

Weak-signal and high-dynamics are of two primary concerns of space navigation using GNSS (Global Navigation Satellite System) in the space service volume (SSV). The paper firstly defines a reference assumption third-order phase-locked loop (PLL) as the baseline of an onboard GNSS receiver, and proves the incompetence of this conventional architecture. Then an adaptive four-state Kalman filter (KF)-based algorithm is introduced to realize the optimization of loop noise bandwidth, which can adaptively regulate its filter gain according to the received signal power and line-of-sight (LOS) dynamics. To overcome the matter of losing lock in weak-signal and high-dynamic environments, an open loop tracking strategy aided by an inertial navigation system (INS) is recommended, and the traditional maximum likelihood estimation (MLE) method is modified in a non-coherent way by reconstructing the likelihood cost function. Furthermore, a typical mission with combined orbital maneuvering and non-maneuvering arcs is taken as a destination object to test the two proposed strategies. Finally, the experiment based on computer simulation identifies the effectiveness of an adaptive four-state KF-based strategy under non-maneuvering conditions and the virtue of INS-assisted methods under maneuvering conditions.

Analysing and controlling the tax evasion dynamics via majority-vote model

NASA Astrophysics Data System (ADS)

Lima, F. W. S.

2010-09-01

Within the context of agent-based Monte-Carlo simulations, we study the well-known majority-vote model (MVM) with noise applied to tax evasion on simple square lattices, Voronoi-Delaunay random lattices, Barabasi-Albert networks, and Erdös-Rényi random graphs. In the order to analyse and to control the fluctuations for tax evasion in the economics model proposed by Zaklan, MVM is applied in the neighborhod of the noise critical qc to evolve the Zaklan model. The Zaklan model had been studied recently using the equilibrium Ising model. Here we show that the Zaklan model is robust because this can be studied using equilibrium dynamics of Ising model also through the nonequilibrium MVM and on various topologies cited above giving the same behavior regardless of dynamic or topology used here.

Dynamic mesolimbic dopamine signaling during action sequence learning and expectation violation

PubMed Central

Collins, Anne L.; Greenfield, Venuz Y.; Bye, Jeffrey K.; Linker, Kay E.; Wang, Alice S.; Wassum, Kate M.

2016-01-01

Prolonged mesolimbic dopamine concentration changes have been detected during spatial navigation, but little is known about the conditions that engender this signaling profile or how it develops with learning. To address this, we monitored dopamine concentration changes in the nucleus accumbens core of rats throughout acquisition and performance of an instrumental action sequence task. Prolonged dopamine concentration changes were detected that ramped up as rats executed each action sequence and declined after earned reward collection. With learning, dopamine concentration began to rise increasingly earlier in the execution of the sequence and ultimately backpropagated away from stereotyped sequence actions, becoming only transiently elevated by the most distal and unexpected reward predictor. Action sequence-related dopamine signaling was reactivated in well-trained rats if they became disengaged in the task and in response to an unexpected change in the value, but not identity of the earned reward. Throughout training and test, dopamine signaling correlated with sequence performance. These results suggest that action sequences can engender a prolonged mode of dopamine signaling in the nucleus accumbens core and that such signaling relates to elements of the motivation underlying sequence execution and is dynamic with learning, overtraining and violations in reward expectation. PMID:26869075

Endocannabinoid signaling and memory dynamics: A synaptic perspective.

PubMed

Drumond, Ana; Madeira, Natália; Fonseca, Rosalina

2017-02-01

Memory acquisition is a key brain feature in which our human nature relies on. Memories evolve over time. Initially after learning, memories are labile and sensitive to disruption by the interference of concurrent events. Later on, after consolidation, memories are resistant to disruption. However, reactivation of previously consolidated memories renders them again in an unstable state and therefore susceptible to perturbation. Additionally, and depending on the characteristics of the stimuli, a parallel process may be initiated which ultimately leads to the extinction of the previously acquired response. This dynamic aspect of memory maintenance opens the possibility for an updating of previously acquired memories but it also creates several conceptual challenges. What is the time window for memory updating? What determines whether reconsolidation or extinction is triggered? In this review, we tried to re-examine the relationship between consolidation, reconsolidation and extinction, aiming for a unifying view of memory dynamics. Since cellular models of memory share common principles, we present the evidence that similar rules apply to the maintenance of synaptic plasticity. Recently, a new function of the endocannabinoid (eCB) signaling system has been described for associative forms of synaptic plasticity in amygdala synapses. The eCB system has emerged as a key modulator of memory dynamics by adjusting the outcome to stimuli intensity. We propose a key function of eCB in discriminative forms of learning by restricting associative plasticity in amygdala synapses. Since many neuropsychiatric disorders are associated with a dysregulation in memory dynamics, understanding the rules underlying memory maintenance paves the path to better clinical interventions. Copyright © 2016 Elsevier Inc. All rights reserved.

The Membrane Skeleton Controls Diffusion Dynamics and Signaling through the B Cell Receptor

PubMed Central

Treanor, Bebhinn; Depoil, David; Gonzalez-Granja, Aitor; Barral, Patricia; Weber, Michele; Dushek, Omer; Bruckbauer, Andreas; Batista, Facundo D.

2010-01-01

Summary Early events of B cell activation after B cell receptor (BCR) triggering have been well characterized. However, little is known about the steady state of the BCR on the cell surface. Here, we simultaneously visualize single BCR particles and components of the membrane skeleton. We show that an ezrin- and actin-defined network influenced steady-state BCR diffusion by creating boundaries that restrict BCR diffusion. We identified the intracellular domain of Igβ as important in mediating this restriction in diffusion. Importantly, alteration of this network was sufficient to induce robust intracellular signaling and concomitant increase in BCR mobility. Moreover, by using B cells deficient in key signaling molecules, we show that this signaling was most probably initiated by the BCR. Thus, our results suggest the membrane skeleton plays a crucial function in controlling BCR dynamics and thereby signaling, in a way that could be important for understanding tonic signaling necessary for B cell development and survival. PMID:20171124

Fluid dynamics alter Caenorhabditis elegans body length via TGF-β/DBL-1 neuromuscular signaling

PubMed Central

Harada, Shunsuke; Hashizume, Toko; Nemoto, Kanako; Shao, Zhenhua; Higashitani, Nahoko; Etheridge, Timothy; Szewczyk, Nathaniel J; Fukui, Keiji; Higashibata, Akira; Higashitani, Atsushi

2016-01-01

Skeletal muscle wasting is a major obstacle for long-term space exploration. Similar to astronauts, the nematode Caenorhabditis elegans displays negative muscular and physical effects when in microgravity in space. It remains unclear what signaling molecules and behavior(s) cause these negative alterations. Here we studied key signaling molecules involved in alterations of C. elegans physique in response to fluid dynamics in ground-based experiments. Placing worms in space on a 1G accelerator increased a myosin heavy chain, myo-3, and a transforming growth factor-β (TGF-β), dbl-1, gene expression. These changes also occurred when the fluid dynamic parameters viscosity/drag resistance or depth of liquid culture were increased on the ground. In addition, body length increased in wild type and body wall cuticle collagen mutants, rol-6 and dpy-5, grown in liquid culture. In contrast, body length did not increase in TGF-β, dbl-1, or downstream signaling pathway, sma-4/Smad, mutants. Similarly, a D1-like dopamine receptor, DOP-4, and a mechanosensory channel, UNC-8, were required for increased dbl-1 expression and altered physique in liquid culture. As C. elegans contraction rates are much higher when swimming in liquid than when crawling on an agar surface, we also examined the relationship between body length enhancement and rate of contraction. Mutants with significantly reduced contraction rates were typically smaller. However, in dop-4, dbl-1, and sma-4 mutants, contraction rates still increased in liquid. These results suggest that neuromuscular signaling via TGF-β/DBL-1 acts to alter body physique in response to environmental conditions including fluid dynamics. PMID:28725724

Dynamic Characteristics of Buildings from Signal Processing of Ambient Vibration

NASA Astrophysics Data System (ADS)

Dobre, Daniela; Sorin Dragomir, Claudiu

2017-10-01

The experimental technique used to determine the dynamic characteristics of buildings is based on records of low intensity oscillations of the building produced by various natural factors, such as permanent agitation type microseismic motions, city traffic, wind etc. The possibility of recording these oscillations is provided by the latest seismic stations (Geosig and Kinemetrics digital accelerographs). The permanent microseismic agitation of the soil is a complex form of stationary random oscillations. The building filters the soil excitation, selects and increases the components of disruptive vibrations corresponding to its natural vibration periods. For some selected buildings, with different instrumentation schemes for the location of sensors (in free-field, at basement, ground floor, roof level), a correlation between the dynamic characteristics resulted from signal processing of ambient vibration and from a theoretical analysis will be presented. The interpretation of recording results could highlight the behavior of the whole structure. On the other hand, these results are compared with those from strong motions, or obtained from a complex dynamic analysis, and they are quite different, but they are explicable.

Weak and Dynamic GNSS Signal Tracking Strategies for Flight Missions in the Space Service Volume

PubMed Central

Jing, Shuai; Zhan, Xingqun; Liu, Baoyu; Chen, Maolin

2016-01-01

Weak-signal and high-dynamics are of two primary concerns of space navigation using GNSS (Global Navigation Satellite System) in the space service volume (SSV). The paper firstly defines a reference assumption third-order phase-locked loop (PLL) as the baseline of an onboard GNSS receiver, and proves the incompetence of this conventional architecture. Then an adaptive four-state Kalman filter (KF)-based algorithm is introduced to realize the optimization of loop noise bandwidth, which can adaptively regulate its filter gain according to the received signal power and line-of-sight (LOS) dynamics. To overcome the matter of losing lock in weak-signal and high-dynamic environments, an open loop tracking strategy aided by an inertial navigation system (INS) is recommended, and the traditional maximum likelihood estimation (MLE) method is modified in a non-coherent way by reconstructing the likelihood cost function. Furthermore, a typical mission with combined orbital maneuvering and non-maneuvering arcs is taken as a destination object to test the two proposed strategies. Finally, the experiment based on computer simulation identifies the effectiveness of an adaptive four-state KF-based strategy under non-maneuvering conditions and the virtue of INS-assisted methods under maneuvering conditions. PMID:27598164

Data-driven reverse engineering of signaling pathways using ensembles of dynamic models.

PubMed

Henriques, David; Villaverde, Alejandro F; Rocha, Miguel; Saez-Rodriguez, Julio; Banga, Julio R

2017-02-01

Despite significant efforts and remarkable progress, the inference of signaling networks from experimental data remains very challenging. The problem is particularly difficult when the objective is to obtain a dynamic model capable of predicting the effect of novel perturbations not considered during model training. The problem is ill-posed due to the nonlinear nature of these systems, the fact that only a fraction of the involved proteins and their post-translational modifications can be measured, and limitations on the technologies used for growing cells in vitro, perturbing them, and measuring their variations. As a consequence, there is a pervasive lack of identifiability. To overcome these issues, we present a methodology called SELDOM (enSEmbLe of Dynamic lOgic-based Models), which builds an ensemble of logic-based dynamic models, trains them to experimental data, and combines their individual simulations into an ensemble prediction. It also includes a model reduction step to prune spurious interactions and mitigate overfitting. SELDOM is a data-driven method, in the sense that it does not require any prior knowledge of the system: the interaction networks that act as scaffolds for the dynamic models are inferred from data using mutual information. We have tested SELDOM on a number of experimental and in silico signal transduction case-studies, including the recent HPN-DREAM breast cancer challenge. We found that its performance is highly competitive compared to state-of-the-art methods for the purpose of recovering network topology. More importantly, the utility of SELDOM goes beyond basic network inference (i.e. uncovering static interaction networks): it builds dynamic (based on ordinary differential equation) models, which can be used for mechanistic interpretations and reliable dynamic predictions in new experimental conditions (i.e. not used in the training). For this task, SELDOM's ensemble prediction is not only consistently better than predictions

Data-driven reverse engineering of signaling pathways using ensembles of dynamic models

PubMed Central

Henriques, David; Villaverde, Alejandro F.; Banga, Julio R.

2017-01-01

Despite significant efforts and remarkable progress, the inference of signaling networks from experimental data remains very challenging. The problem is particularly difficult when the objective is to obtain a dynamic model capable of predicting the effect of novel perturbations not considered during model training. The problem is ill-posed due to the nonlinear nature of these systems, the fact that only a fraction of the involved proteins and their post-translational modifications can be measured, and limitations on the technologies used for growing cells in vitro, perturbing them, and measuring their variations. As a consequence, there is a pervasive lack of identifiability. To overcome these issues, we present a methodology called SELDOM (enSEmbLe of Dynamic lOgic-based Models), which builds an ensemble of logic-based dynamic models, trains them to experimental data, and combines their individual simulations into an ensemble prediction. It also includes a model reduction step to prune spurious interactions and mitigate overfitting. SELDOM is a data-driven method, in the sense that it does not require any prior knowledge of the system: the interaction networks that act as scaffolds for the dynamic models are inferred from data using mutual information. We have tested SELDOM on a number of experimental and in silico signal transduction case-studies, including the recent HPN-DREAM breast cancer challenge. We found that its performance is highly competitive compared to state-of-the-art methods for the purpose of recovering network topology. More importantly, the utility of SELDOM goes beyond basic network inference (i.e. uncovering static interaction networks): it builds dynamic (based on ordinary differential equation) models, which can be used for mechanistic interpretations and reliable dynamic predictions in new experimental conditions (i.e. not used in the training). For this task, SELDOM’s ensemble prediction is not only consistently better than predictions

TLR4 signaling shapes B cell dynamics via MyD88-dependent pathways and Rac GTPases.

PubMed

Barrio, Laura; Saez de Guinoa, Julia; Carrasco, Yolanda R

2013-10-01

B cells use a plethora of TLR to recognize pathogen-derived ligands. These innate signals have an important function in the B cell adaptive immune response and modify their trafficking and tissue location. The direct role of TLR signaling on B cell dynamics nonetheless remains almost entirely unknown. In this study, we used a state-of-the-art two-dimensional model combined with real-time microscopy to study the effect of TLR4 stimulation on mouse B cell motility in response to chemokines. We show that a minimum stimulation period is necessary for TLR4 modification of B cell behavior. TLR4 stimulation increased B cell polarization, migration, and directionality; these increases were dependent on the MyD88 signaling pathway and did not require ERK or p38 MAPK activity downstream of TLR4. In addition, TLR4 stimulation enhanced Rac GTPase activity and promoted sustained Rac activation in response to chemokines. These results increase our understanding of the regulation of B cell dynamics by innate signals and the underlying molecular mechanisms.

S-EMG signal compression based on domain transformation and spectral shape dynamic bit allocation

PubMed Central

2014-01-01

Background Surface electromyographic (S-EMG) signal processing has been emerging in the past few years due to its non-invasive assessment of muscle function and structure and because of the fast growing rate of digital technology which brings about new solutions and applications. Factors such as sampling rate, quantization word length, number of channels and experiment duration can lead to a potentially large volume of data. Efficient transmission and/or storage of S-EMG signals are actually a research issue. That is the aim of this work. Methods This paper presents an algorithm for the data compression of surface electromyographic (S-EMG) signals recorded during isometric contractions protocol and during dynamic experimental protocols such as the cycling activity. The proposed algorithm is based on discrete wavelet transform to proceed spectral decomposition and de-correlation, on a dynamic bit allocation procedure to code the wavelets transformed coefficients, and on an entropy coding to minimize the remaining redundancy and to pack all data. The bit allocation scheme is based on mathematical decreasing spectral shape models, which indicates a shorter digital word length to code high frequency wavelets transformed coefficients. Four bit allocation spectral shape methods were implemented and compared: decreasing exponential spectral shape, decreasing linear spectral shape, decreasing square-root spectral shape and rotated hyperbolic tangent spectral shape. Results The proposed method is demonstrated and evaluated for an isometric protocol and for a dynamic protocol using a real S-EMG signal data bank. Objective performance evaluations metrics are presented. In addition, comparisons with other encoders proposed in scientific literature are shown. Conclusions The decreasing bit allocation shape applied to the quantized wavelet coefficients combined with arithmetic coding results is an efficient procedure. The performance comparisons of the proposed S-EMG data

Requirements for implementation of Kuessner and Wagner indicial lift growth functions into the FLEXSTAB computer program system for use in dynamic loads analyses

NASA Technical Reports Server (NTRS)

Miller, R. D.; Rogers, J. T.

1975-01-01

General requirements for dynamic loads analyses are described. The indicial lift growth function unsteady subsonic aerodynamic representation is reviewed, and the FLEXSTAB CPS is evaluated with respect to these general requirements. The effects of residual flexibility techniques on dynamic loads analyses are also evaluated using a simple dynamic model.

Measuring Dynamic Signals with Direct Sensor-to-Microcontroller Interfaces Applied to a Magnetoresistive Sensor

PubMed Central

Sifuentes, Ernesto; Gonzalez-Landaeta, Rafael; Cota-Ruiz, Juan; Reverter, Ferran

2017-01-01

This paper evaluates the performance of direct interface circuits (DIC), where the sensor is directly connected to a microcontroller, when a resistive sensor subjected to dynamic changes is measured. The theoretical analysis provides guidelines for the selection of the components taking into account both the desired resolution and the bandwidth of the input signal. Such an analysis reveals that there is a trade-off between the sampling frequency and the resolution of the measurement, and this depends on the selected value of the capacitor that forms the RC circuit together with the sensor resistance. This performance is then experimentally proved with a DIC measuring a magnetoresistive sensor exposed to a magnetic field of different frequencies, amplitudes, and waveforms. A sinusoidal magnetic field up to 1 kHz can be monitored with a resolution of eight bits and a sampling frequency of around 10 kSa/s. If a higher resolution is desired, the sampling frequency has to be lower, thus limiting the bandwidth of the dynamic signal under measurement. The DIC is also applied to measure an electrocardiogram-type signal and its QRS complex is well identified, which enables the estimation, for instance, of the heart rate. PMID:28524078

Measuring Dynamic Signals with Direct Sensor-to-Microcontroller Interfaces Applied to a Magnetoresistive Sensor.

PubMed

Sifuentes, Ernesto; Gonzalez-Landaeta, Rafael; Cota-Ruiz, Juan; Reverter, Ferran

2017-05-18

This paper evaluates the performance of direct interface circuits (DIC), where the sensor is directly connected to a microcontroller, when a resistive sensor subjected to dynamic changes is measured. The theoretical analysis provides guidelines for the selection of the components taking into account both the desired resolution and the bandwidth of the input signal. Such an analysis reveals that there is a trade-off between the sampling frequency and the resolution of the measurement, and this depends on the selected value of the capacitor that forms the RC circuit together with the sensor resistance. This performance is then experimentally proved with a DIC measuring a magnetoresistive sensor exposed to a magnetic field of different frequencies, amplitudes, and waveforms. A sinusoidal magnetic field up to 1 kHz can be monitored with a resolution of eight bits and a sampling frequency of around 10 kSa/s. If a higher resolution is desired, the sampling frequency has to be lower, thus limiting the bandwidth of the dynamic signal under measurement. The DIC is also applied to measure an electrocardiogram-type signal and its QRS complex is well identified, which enables the estimation, for instance, of the heart rate.

Epileptic seizures as condensed sleep: an analysis of network dynamics from electroencephalogram signals.

PubMed

Gast, Heidemarie; Müller, Markus; Rummel, Christian; Roth, Corinne; Mathis, Johannes; Schindler, Kaspar; Bassetti, Claudio L

2014-06-01

Both deepening sleep and evolving epileptic seizures are associated with increasing slow-wave activity. Larger-scale functional networks derived from electroencephalogram indicate that in both transitions dramatic changes of communication between brain areas occur. During seizures these changes seem to be 'condensed', because they evolve more rapidly than during deepening sleep. Here we set out to assess quantitatively functional network dynamics derived from electroencephalogram signals during seizures and normal sleep. Functional networks were derived from electroencephalogram signals from wakefulness, light and deep sleep of 12 volunteers, and from pre-seizure, seizure and post-seizure time periods of 10 patients suffering from focal onset pharmaco-resistant epilepsy. Nodes of the functional network represented electrical signals recorded by single electrodes and were linked if there was non-random cross-correlation between the two corresponding electroencephalogram signals. Network dynamics were then characterized by the evolution of global efficiency, which measures ease of information transmission. Global efficiency was compared with relative delta power. Global efficiency significantly decreased both between light and deep sleep, and between pre-seizure, seizure and post-seizure time periods. The decrease of global efficiency was due to a loss of functional links. While global efficiency decreased significantly, relative delta power increased except between the time periods wakefulness and light sleep, and pre-seizure and seizure. Our results demonstrate that both epileptic seizures and deepening sleep are characterized by dramatic fragmentation of larger-scale functional networks, and further support the similarities between sleep and seizures. © 2013 European Sleep Research Society.

Dynamics and spatial structure of ENSO from re-analyses versus CMIP5 models

NASA Astrophysics Data System (ADS)

Serykh, Ilya; Sonechkin, Dmitry

2016-04-01

Basing on a mathematical idea about the so-called strange nonchaotic attractor (SNA) in the quasi-periodically forced dynamical systems, the currently available re-analyses data are considered. It is found that the El Niño - Southern Oscillation (ENSO) is driven not only by the seasonal heating, but also by three more external periodicities (incommensurate to the annual period) associated with the ~18.6-year lunar-solar nutation of the Earth rotation axis, ~11-year sunspot activity cycle and the ~14-month Chandler wobble in the Earth's pole motion. Because of the incommensurability of their periods all four forces affect the system in inappropriate time moments. As a result, the ENSO time series look to be very complex (strange in mathematical terms) but nonchaotic. The power spectra of ENSO indices reveal numerous peaks located at the periods that are multiples of the above periodicities as well as at their sub- and super-harmonic. In spite of the above ENSO complexity, a mutual order seems to be inherent to the ENSO time series and their spectra. This order reveals itself in the existence of a scaling of the power spectrum peaks and respective rhythms in the ENSO dynamics that look like the power spectrum and dynamics of the SNA. It means there are no limits to forecast ENSO, in principle. In practice, it opens a possibility to forecast ENSO for several years ahead. Global spatial structures of anomalies during El Niño and power spectra of ENSO indices from re-analyses are compared with the respective output quantities in the CMIP5 climate models (the Historical experiment). It is found that the models reproduce global spatial structures of the near surface temperature and sea level pressure anomalies during El Niño very similar to these fields in the re-analyses considered. But the power spectra of the ENSO indices from the CMIP5 models show no peaks at the same periods as the re-analyses power spectra. We suppose that it is possible to improve modeled

Characterising Dynamic Instability in High Water-Cut Oil-Water Flows Using High-Resolution Microwave Sensor Signals

NASA Astrophysics Data System (ADS)

Liu, Weixin; Jin, Ningde; Han, Yunfeng; Ma, Jing

2018-06-01

In the present study, multi-scale entropy algorithm was used to characterise the complex flow phenomena of turbulent droplets in high water-cut oil-water two-phase flow. First, we compared multi-scale weighted permutation entropy (MWPE), multi-scale approximate entropy (MAE), multi-scale sample entropy (MSE) and multi-scale complexity measure (MCM) for typical nonlinear systems. The results show that MWPE presents satisfied variability with scale and anti-noise ability. Accordingly, we conducted an experiment of vertical upward oil-water two-phase flow with high water-cut and collected the signals of a high-resolution microwave resonant sensor, based on which two indexes, the entropy rate and mean value of MWPE, were extracted. Besides, the effects of total flow rate and water-cut on these two indexes were analysed. Our researches show that MWPE is an effective method to uncover the dynamic instability of oil-water two-phase flow with high water-cut.

EMD-Based Symbolic Dynamic Analysis for the Recognition of Human and Nonhuman Pyroelectric Infrared Signals.

PubMed

Zhao, Jiaduo; Gong, Weiguo; Tang, Yuzhen; Li, Weihong

2016-01-20

In this paper, we propose an effective human and nonhuman pyroelectric infrared (PIR) signal recognition method to reduce PIR detector false alarms. First, using the mathematical model of the PIR detector, we analyze the physical characteristics of the human and nonhuman PIR signals; second, based on the analysis results, we propose an empirical mode decomposition (EMD)-based symbolic dynamic analysis method for the recognition of human and nonhuman PIR signals. In the proposed method, first, we extract the detailed features of a PIR signal into five symbol sequences using an EMD-based symbolization method, then, we generate five feature descriptors for each PIR signal through constructing five probabilistic finite state automata with the symbol sequences. Finally, we use a weighted voting classification strategy to classify the PIR signals with their feature descriptors. Comparative experiments show that the proposed method can effectively classify the human and nonhuman PIR signals and reduce PIR detector's false alarms.

Dynamic characteristics of T2*-weighted signal in calf muscles of peripheral artery disease during low-intensity exercise.

PubMed

Li, Zhijun; Muller, Matthew D; Wang, Jianli; Sica, Christopher T; Karunanayaka, Prasanna; Sinoway, Lawrence I; Yang, Qing X

2017-07-01

To evaluate the dynamic characteristics of T2* -weighted signal change in exercising skeletal muscle of healthy subjects and peripheral artery disease (PAD) patients under a low-intensity exercise paradigm. Nine PAD patients and nine age- and sex-matched healthy volunteers underwent a low-intensity exercise paradigm while magnetic resonance imaging (MRI) (3.0T) was obtained. T2*-weighted signal time-courses in lateral gastrocnemius, medial gastrocnemius, soleus, and tibialis anterior were acquired and analyzed. Correlations were performed between dynamic T2*-weighted signal and changes in heart rate, mean arterial pressure, leg pain, and perceived exertion. A significant signal decrease was observed during exercise in soleus and tibialis anterior of healthy participants (P = 0.0007-0.04 and 0.001-0.009, respectively). In PAD, negative signals were observed (P = 0.008-0.02 and 0.003-0.01, respectively) in soleus and lateral gastrocnemius during the early exercise stage. Then the signal gradually increased above the baseline in the lateral gastrocnemius during and after exercise in six of the eight patients who completed the study. This signal increase in patients' lateral gastrocnemius was significantly greater than in healthy subjects' during the later exercise stage (two-sample t-tests, P = 0.001-0.03). Heart rate and mean arterial pressure responses to exercise were significantly higher in PAD than healthy subjects (P = 0.036 and 0.008, respectively) and the patients experienced greater leg pain and exertion (P = 0.006 and P = 0.0014, respectively). During low-intensity exercise, there were different dynamic T2*-weighted signal behavior in the healthy and PAD exercising muscles. 2 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:40-48. © 2016 International Society for Magnetic Resonance in Medicine.

A system of recurrent neural networks for modularising, parameterising and dynamic analysis of cell signalling networks.

PubMed

Samarasinghe, S; Ling, H

In this paper, we show how to extend our previously proposed novel continuous time Recurrent Neural Networks (RNN) approach that retains the advantage of continuous dynamics offered by Ordinary Differential Equations (ODE) while enabling parameter estimation through adaptation, to larger signalling networks using a modular approach. Specifically, the signalling network is decomposed into several sub-models based on important temporal events in the network. Each sub-model is represented by the proposed RNN and trained using data generated from the corresponding ODE model. Trained sub-models are assembled into a whole system RNN which is then subjected to systems dynamics and sensitivity analyses. The concept is illustrated by application to G1/S transition in cell cycle using Iwamoto et al. (2008) ODE model. We decomposed the G1/S network into 3 sub-models: (i) E2F transcription factor release; (ii) E2F and CycE positive feedback loop for elevating cyclin levels; and (iii) E2F and CycA negative feedback to degrade E2F. The trained sub-models accurately represented system dynamics and parameters were in good agreement with the ODE model. The whole system RNN however revealed couple of parameters contributing to compounding errors due to feedback and required refinement to sub-model 2. These related to the reversible reaction between CycE/CDK2 and p27, its inhibitor. The revised whole system RNN model very accurately matched dynamics of the ODE system. Local sensitivity analysis of the whole system model further revealed the most dominant influence of the above two parameters in perturbing G1/S transition, giving support to a recent hypothesis that the release of inhibitor p27 from Cyc/CDK complex triggers cell cycle stage transition. To make the model useful in a practical setting, we modified each RNN sub-model with a time relay switch to facilitate larger interval input data (≈20min) (original model used data for 30s or less) and retrained them that produced

Dynamic protein interaction networks and new structural paradigms in signaling

PubMed Central

Csizmok, Veronika; Follis, Ariele Viacava; Kriwacki, Richard W.; Forman-Kay, Julie D.

2017-01-01

Understanding signaling and other complex biological processes requires elucidating the critical roles of intrinsically disordered proteins and regions (IDPs/IDRs), which represent ~30% of the proteome and enable unique regulatory mechanisms. In this review we describe the structural heterogeneity of disordered proteins that underpins these mechanisms and the latest progress in obtaining structural descriptions of ensembles of disordered proteins that are needed for linking structure and dynamics to function. We describe the diverse interactions of IDPs that can have unusual characteristics such as “ultrasensitivity” and “regulated folding and unfolding”. We also summarize the mounting data showing that large-scale assembly and protein phase separation occurs within a variety of signaling complexes and cellular structures. In addition, we discuss efforts to therapeutically target disordered proteins with small molecules. Overall, we interpret the remodeling of disordered state ensembles due to binding and post-translational modifications within an expanded framework for allostery that provides significant insights into how disordered proteins transmit biological information. PMID:26922996

Quantum dot SOA input power dynamic range improvement for differential-phase encoded signals.

PubMed

Vallaitis, T; Bonk, R; Guetlein, J; Hillerkuss, D; Li, J; Brenot, R; Lelarge, F; Duan, G H; Freude, W; Leuthold, J

2010-03-15

Experimentally we find a 10 dB input power dynamic range advantage for amplification of phase encoded signals with quantum dot SOA as compared to low-confinement bulk SOA. An analysis of amplitude and phase effects shows that this improvement can be attributed to the lower alpha-factor found in QD SOA.

Dynamic shaping of dopamine signals during probabilistic Pavlovian conditioning.

PubMed

Hart, Andrew S; Clark, Jeremy J; Phillips, Paul E M

2015-01-01

Cue- and reward-evoked phasic dopamine activity during Pavlovian and operant conditioning paradigms is well correlated with reward-prediction errors from formal reinforcement learning models, which feature teaching signals in the form of discrepancies between actual and expected reward outcomes. Additionally, in learning tasks where conditioned cues probabilistically predict rewards, dopamine neurons show sustained cue-evoked responses that are correlated with the variance of reward and are maximal to cues predicting rewards with a probability of 0.5. Therefore, it has been suggested that sustained dopamine activity after cue presentation encodes the uncertainty of impending reward delivery. In the current study we examined the acquisition and maintenance of these neural correlates using fast-scan cyclic voltammetry in rats implanted with carbon fiber electrodes in the nucleus accumbens core during probabilistic Pavlovian conditioning. The advantage of this technique is that we can sample from the same animal and recording location throughout learning with single trial resolution. We report that dopamine release in the nucleus accumbens core contains correlates of both expected value and variance. A quantitative analysis of these signals throughout learning, and during the ongoing updating process after learning in probabilistic conditions, demonstrates that these correlates are dynamically encoded during these phases. Peak CS-evoked responses are correlated with expected value and predominate during early learning while a variance-correlated sustained CS signal develops during the post-asymptotic updating phase. Copyright © 2014 Elsevier Inc. All rights reserved.

Dynamics Determine Signaling in a Multicomponent System Associated with Rheumatoid Arthritis.

PubMed

Lindgren, Cecilia; Tyagi, Mohit; Viljanen, Johan; Toms, Johannes; Ge, Changrong; Zhang, Naru; Holmdahl, Rikard; Kihlberg, Jan; Linusson, Anna

2018-05-24

Strategies that target multiple components are usually required for treatment of diseases originating from complex biological systems. The multicomponent system consisting of the DR4 major histocompatibility complex type II molecule, the glycopeptide CII259-273 from type II collagen, and a T-cell receptor is associated with development of rheumatoid arthritis (RA). We introduced non-native amino acids and amide bond isosteres into CII259-273 and investigated the effect on binding to DR4 and the subsequent T-cell response. Molecular dynamics simulations revealed that complexes between DR4 and derivatives of CII259-273 were highly dynamic. Signaling in the overall multicomponent system was found to depend on formation of an appropriate number of dynamic intramolecular hydrogen bonds between DR4 and CII259-273, together with the positioning of the galactose moiety of CII259-273 in the DR4 binding groove. Interestingly, the system tolerated modifications at several positions in CII259-273, indicating opportunities to use analogues to increase our understanding of how rheumatoid arthritis develops and for evaluation as vaccines to treat RA.

Strength and dynamic characteristics analyses of wound composite axial impeller

NASA Astrophysics Data System (ADS)

Wang, Jifeng; Olortegui-Yume, Jorge; Müller, Norbert

2012-03-01

A low cost, light weight, high performance composite material turbomachinery impeller with a uniquely designed blade patterns is analyzed. Such impellers can economically enable refrigeration plants to use water as a refrigerant (R718). A strength and dynamic characteristics analyses procedure is developed to assess the maximum stresses and natural frequencies of these wound composite axial impellers under operating loading conditions. Numerical simulation using FEM for two-dimensional and three-dimensional impellers was investigated. A commercially available software ANSYS is used for the finite element calculations. Analysis is done for different blade geometries and then suggestions are made for optimum design parameters. In order to avoid operating at resonance, which can make impellers suffer a significant reduction in the design life, the designer must calculate the natural frequency and modal shape of the impeller to analyze the dynamic characteristics. The results show that using composite Kevlar fiber/epoxy matrix enables the impeller to run at high tip speed and withstand the stresses, no critical speed will be matched during start-up and shut-down, and that mass imbalances of the impeller shall not pose a critical problem.

Time series analyses of breathing patterns of lung cancer patients using nonlinear dynamical system theory.

PubMed

Tewatia, D K; Tolakanahalli, R P; Paliwal, B R; Tomé, W A

2011-04-07

The underlying requirements for successful implementation of any efficient tumour motion management strategy are regularity and reproducibility of a patient's breathing pattern. The physiological act of breathing is controlled by multiple nonlinear feedback and feed-forward couplings. It would therefore be appropriate to analyse the breathing pattern of lung cancer patients in the light of nonlinear dynamical system theory. The purpose of this paper is to analyse the one-dimensional respiratory time series of lung cancer patients based on nonlinear dynamics and delay coordinate state space embedding. It is very important to select a suitable pair of embedding dimension 'm' and time delay 'τ' when performing a state space reconstruction. Appropriate time delay and embedding dimension were obtained using well-established methods, namely mutual information and the false nearest neighbour method, respectively. Establishing stationarity and determinism in a given scalar time series is a prerequisite to demonstrating that the nonlinear dynamical system that gave rise to the scalar time series exhibits a sensitive dependence on initial conditions, i.e. is chaotic. Hence, once an appropriate state space embedding of the dynamical system has been reconstructed, we show that the time series of the nonlinear dynamical systems under study are both stationary and deterministic in nature. Once both criteria are established, we proceed to calculate the largest Lyapunov exponent (LLE), which is an invariant quantity under time delay embedding. The LLE for all 16 patients is positive, which along with stationarity and determinism establishes the fact that the time series of a lung cancer patient's breathing pattern is not random or irregular, but rather it is deterministic in nature albeit chaotic. These results indicate that chaotic characteristics exist in the respiratory waveform and techniques based on state space dynamics should be employed for tumour motion management.

Wavelet Analyses and Applications

ERIC Educational Resources Information Center

Bordeianu, Cristian C.; Landau, Rubin H.; Paez, Manuel J.

2009-01-01

It is shown how a modern extension of Fourier analysis known as wavelet analysis is applied to signals containing multiscale information. First, a continuous wavelet transform is used to analyse the spectrum of a nonstationary signal (one whose form changes in time). The spectral analysis of such a signal gives the strength of the signal in each…

Static and dynamic stress analyses of the prototype high head Francis runner based on site measurement

NASA Astrophysics Data System (ADS)

Huang, X.; Oram, C.; Sick, M.

2014-03-01

More efforts are put on hydro-power to balance voltage and frequency within seconds for primary control in modern smart grids. This requires hydraulic turbines to run at off-design conditions. especially at low load or speed-no load. Besides. the tendency of increasing power output and decreasing weight of the turbine runners has also led to the high level vibration problem of the runners. especially high head Francis runners. Therefore. it is important to carry out the static and dynamic stress analyses of prototype high head Francis runners. This paper investigates the static and dynamic stresses on the prototype high head Francis runner based on site measurements and numerical simulations. The site measurements are performed with pressure transducers and strain gauges. Based on the measured results. computational fluid dynamics (CFD) simulations for the flow channel from stay vane to draft tube cone are performed. Static pressure distributions and dynamic pressure pulsations caused by rotor-stator interaction (RSI) are obtained under various operating conditions. With the CFD results. static and dynamic stresses on the runner at different operating points are calculated by means of the finite element method (FEM). The agreement between simulation and measurement is analysed with linear regression method. which indicates that the numerical result agrees well with that of measurement. Furthermore. the maximum static and dynamic stresses on the runner blade are obtained at various operating points. The relations of the maximum stresses and the power output are discussed in detail. The influences of the boundary conditions on the structural behaviour of the runner are also discussed.

Small-Signal Dynamic Analysis of LCC-HVDC with STATCOM at the Inverter Busbar

NASA Astrophysics Data System (ADS)

Liu, Dong; Jiang, Wen; Guo, Chunyi; Rehman, Atiq Ur; Zhao, Chengyong

2018-01-01

This paper develops a linearized small-signal dynamic model of a Line-Commutated-Converter based HVDC (LCC-HVDC) system with STATCOM at the inverter busbar, and validates its accuracy by comparing time-domain responses from small-signal model and PSCAD-based simulation results. Considering the potential impact of Phase-Locked-Loop (PLL) parameters on the study system and the close connection of STATCOM and LCC inverter station at AC busbar, this paper investigates the impact of PLL gains and AC voltage control parameters of STATCOM on the system small-signal stability. The studies show that (i) the PLL gain has highly impact on the study system and smaller PLL gains are preferable; (ii) larger values of both the proportional gain and the integral gain of AC voltage controller of STATCOM could result in oscillation/instability of the system.

A parallel unbalanced digitization architecture to reduce the dynamic range of multiple signals

NASA Astrophysics Data System (ADS)

Vallérian, Mathieu; HuÅ£u, Florin; Villemaud, Guillaume; Miscopein, Benoît; Risset, Tanguy

2016-05-01

Technologies employed in urban sensor networks are permanently evolving, and thus the gateways employed to collect data in such kind of networks have to be very flexible in order to be compliant with the new communication standards. A convenient way to do that is to digitize all the received signals in one shot and then to digitally perform the signal processing, as it is done in software-defined radio (SDR). All signals can be emitted with very different features (bandwidth, modulation type, and power level) in order to respond to the various propagation conditions. Their difference in terms of power levels is a problem when digitizing them together, as no current commercial analog-to-digital converter (ADC) can provide a fine enough resolution to digitize this high dynamic range between the weakest possible signal in the presence of a stronger signal. This paper presents an RF front end receiver architecture capable of handling this problem by using two ADCs of lower resolutions. The architecture is validated through a set of simulations using Keysight's ADS software. The main validation criterion is the bit error rate comparison with a classical receiver.

A robust color signal processing with wide dynamic range WRGB CMOS image sensor

NASA Astrophysics Data System (ADS)

Kawada, Shun; Kuroda, Rihito; Sugawa, Shigetoshi

2011-01-01

We have developed a robust color reproduction methodology by a simple calculation with a new color matrix using the formerly developed wide dynamic range WRGB lateral overflow integration capacitor (LOFIC) CMOS image sensor. The image sensor was fabricated through a 0.18 μm CMOS technology and has a 45 degrees oblique pixel array, the 4.2 μm effective pixel pitch and the W pixels. A W pixel was formed by replacing one of the two G pixels in the Bayer RGB color filter. The W pixel has a high sensitivity through the visible light waveband. An emerald green and yellow (EGY) signal is generated from the difference between the W signal and the sum of RGB signals. This EGY signal mainly includes emerald green and yellow lights. These colors are difficult to be reproduced accurately by the conventional simple linear matrix because their wave lengths are in the valleys of the spectral sensitivity characteristics of the RGB pixels. A new linear matrix based on the EGY-RGB signal was developed. Using this simple matrix, a highly accurate color processing with a large margin to the sensitivity fluctuation and noise has been achieved.

Transmembrane Topology and Signal Peptide Prediction Using Dynamic Bayesian Networks

PubMed Central

Reynolds, Sheila M.; Käll, Lukas; Riffle, Michael E.; Bilmes, Jeff A.; Noble, William Stafford

2008-01-01

Hidden Markov models (HMMs) have been successfully applied to the tasks of transmembrane protein topology prediction and signal peptide prediction. In this paper we expand upon this work by making use of the more powerful class of dynamic Bayesian networks (DBNs). Our model, Philius, is inspired by a previously published HMM, Phobius, and combines a signal peptide submodel with a transmembrane submodel. We introduce a two-stage DBN decoder that combines the power of posterior decoding with the grammar constraints of Viterbi-style decoding. Philius also provides protein type, segment, and topology confidence metrics to aid in the interpretation of the predictions. We report a relative improvement of 13% over Phobius in full-topology prediction accuracy on transmembrane proteins, and a sensitivity and specificity of 0.96 in detecting signal peptides. We also show that our confidence metrics correlate well with the observed precision. In addition, we have made predictions on all 6.3 million proteins in the Yeast Resource Center (YRC) database. This large-scale study provides an overall picture of the relative numbers of proteins that include a signal-peptide and/or one or more transmembrane segments as well as a valuable resource for the scientific community. All DBNs are implemented using the Graphical Models Toolkit. Source code for the models described here is available at http://noble.gs.washington.edu/proj/philius. A Philius Web server is available at http://www.yeastrc.org/philius, and the predictions on the YRC database are available at http://www.yeastrc.org/pdr. PMID:18989393

All-digital signal-processing open-loop fiber-optic gyroscope with enlarged dynamic range.

PubMed

Wang, Qin; Yang, Chuanchuan; Wang, Xinyue; Wang, Ziyu

2013-12-15

We propose and realize a new open-loop fiber-optic gyroscope (FOG) with an all-digital signal-processing (DSP) system where an all-digital phase-locked loop is employed for digital demodulation to eliminate the variation of the source intensity and suppress the bias drift. A Sagnac phase-shift tracking method is proposed to enlarge the dynamic range, and, with its aid, a new open-loop FOG, which can achieve a large dynamic range and high sensitivity at the same time, is realized. The experimental results show that compared with the conventional open-loop FOG with the same fiber coil and optical devices, the proposed FOG reduces the bias instability from 0.259 to 0.018 deg/h, and the angle random walk from 0.031 to 0.006 deg/h(1/2), moreover, enlarges the dynamic range to ±360 deg/s, exceeding the maximum dynamic range ±63 deg/s of the conventional open-loop FOG.

Dynamic complexity: plant receptor complexes at the plasma membrane.

PubMed

Burkart, Rebecca C; Stahl, Yvonne

2017-12-01

Plant receptor complexes at the cell surface perceive many different external and internal signalling molecules and relay these signals into the cell to regulate development, growth and immunity. Recent progress in the analyses of receptor complexes using different live cell imaging approaches have shown that receptor complex formation and composition are dynamic and take place at specific microdomains at the plasma membrane. In this review we focus on three prominent examples of Arabidopsis thaliana receptor complexes and how their dynamic spatio-temporal distribution at the PM has been studied recently. We will elaborate on the newly emerging concept of plasma membrane microdomains as potential hubs for specific receptor complex assembly and signalling outputs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Mapping Transient Hyperventilation Induced Alterations with Estimates of the Multi-Scale Dynamics of BOLD Signal.

PubMed

Kiviniemi, Vesa; Remes, Jukka; Starck, Tuomo; Nikkinen, Juha; Haapea, Marianne; Silven, Olli; Tervonen, Osmo

2009-01-01

Temporal blood oxygen level dependent (BOLD) contrast signals in functional MRI during rest may be characterized by power spectral distribution (PSD) trends of the form 1/f(alpha). Trends with 1/f characteristics comprise fractal properties with repeating oscillation patterns in multiple time scales. Estimates of the fractal properties enable the quantification of phenomena that may otherwise be difficult to measure, such as transient, non-linear changes. In this study it was hypothesized that the fractal metrics of 1/f BOLD signal trends can map changes related to dynamic, multi-scale alterations in cerebral blood flow (CBF) after a transient hyperventilation challenge. Twenty-three normal adults were imaged in a resting-state before and after hyperventilation. Different variables (1/f trend constant alpha, fractal dimension D(f), and, Hurst exponent H) characterizing the trends were measured from BOLD signals. The results show that fractal metrics of the BOLD signal follow the fractional Gaussian noise model, even during the dynamic CBF change that follows hyperventilation. The most dominant effect on the fractal metrics was detected in grey matter, in line with previous hyperventilation vaso-reactivity studies. The alpha was able to differentiate also blood vessels from grey matter changes. D(f) was most sensitive to grey matter. H correlated with default mode network areas before hyperventilation but this pattern vanished after hyperventilation due to a global increase in H. In the future, resting-state fMRI combined with fractal metrics of the BOLD signal may be used for analyzing multi-scale alterations of cerebral blood flow.

Stability, Consistency and Performance of Distribution Entropy in Analysing Short Length Heart Rate Variability (HRV) Signal.

PubMed

Karmakar, Chandan; Udhayakumar, Radhagayathri K; Li, Peng; Venkatesh, Svetha; Palaniswami, Marimuthu

2017-01-01

Distribution entropy ( DistEn ) is a recently developed measure of complexity that is used to analyse heart rate variability (HRV) data. Its calculation requires two input parameters-the embedding dimension m , and the number of bins M which replaces the tolerance parameter r that is used by the existing approximation entropy ( ApEn ) and sample entropy ( SampEn ) measures. The performance of DistEn can also be affected by the data length N . In our previous studies, we have analyzed stability and performance of DistEn with respect to one parameter ( m or M ) or combination of two parameters ( N and M ). However, impact of varying all the three input parameters on DistEn is not yet studied. Since DistEn is predominantly aimed at analysing short length heart rate variability (HRV) signal, it is important to comprehensively study the stability, consistency and performance of the measure using multiple case studies. In this study, we examined the impact of changing input parameters on DistEn for synthetic and physiological signals. We also compared the variations of DistEn and performance in distinguishing physiological (Elderly from Young) and pathological (Healthy from Arrhythmia) conditions with ApEn and SampEn . The results showed that DistEn values are minimally affected by the variations of input parameters compared to ApEn and SampEn. DistEn also showed the most consistent and the best performance in differentiating physiological and pathological conditions with various of input parameters among reported complexity measures. In conclusion, DistEn is found to be the best measure for analysing short length HRV time series.

Stability, Consistency and Performance of Distribution Entropy in Analysing Short Length Heart Rate Variability (HRV) Signal

PubMed Central

Karmakar, Chandan; Udhayakumar, Radhagayathri K.; Li, Peng; Venkatesh, Svetha; Palaniswami, Marimuthu

2017-01-01

Distribution entropy (DistEn) is a recently developed measure of complexity that is used to analyse heart rate variability (HRV) data. Its calculation requires two input parameters—the embedding dimension m, and the number of bins M which replaces the tolerance parameter r that is used by the existing approximation entropy (ApEn) and sample entropy (SampEn) measures. The performance of DistEn can also be affected by the data length N. In our previous studies, we have analyzed stability and performance of DistEn with respect to one parameter (m or M) or combination of two parameters (N and M). However, impact of varying all the three input parameters on DistEn is not yet studied. Since DistEn is predominantly aimed at analysing short length heart rate variability (HRV) signal, it is important to comprehensively study the stability, consistency and performance of the measure using multiple case studies. In this study, we examined the impact of changing input parameters on DistEn for synthetic and physiological signals. We also compared the variations of DistEn and performance in distinguishing physiological (Elderly from Young) and pathological (Healthy from Arrhythmia) conditions with ApEn and SampEn. The results showed that DistEn values are minimally affected by the variations of input parameters compared to ApEn and SampEn. DistEn also showed the most consistent and the best performance in differentiating physiological and pathological conditions with various of input parameters among reported complexity measures. In conclusion, DistEn is found to be the best measure for analysing short length HRV time series. PMID:28979215

I. Advances in NMR Signal Processing. II. Spin Dynamics in Quantum Dissipative Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Yung-Ya

1998-11-01

Part I. Advances in IVMR Signal Processing. Improvements of sensitivity and resolution are two major objects in the development of NMR/MRI. A signal enhancement method is first presented which recovers signal from noise by a judicious combination of a priordmowledge to define the desired feasible solutions and a set theoretic estimation for restoring signal properties that have been lost due to noise contamination. The effect of noise can be significantly mitigated through the process of iteratively modifying the noisy data set to the smallest degree necessary so that it possesses a collection of prescribed properties and also lies closest tomore » the original data set. A novel detection-estimation scheme is then introduced to analyze noisy and/or strongly damped or truncated FIDs. Based on exponential modeling, the number of signals is detected based on information estimated using the matrix pencil method. theory and the spectral parameters are Part II. Spin Dynamics in body dipole-coupled systems Quantum Dissipative Systems. Spin dynamics in manyconstitutes one of the most fundamental problems in magnetic resonance and condensed-matter physics. Its many-spin nature precludes any rigorous treatment. ‘Therefore, the spin-boson model is adopted to describe in the rotating frame the influence of the dipolar local fields on a tagged spin. Based on the polaronic transform and a perturbation treatment, an analytical solution is derived, suggesting the existence of self-trapped states in the. strong coupling limit, i.e., when transverse local field >> longitudinal local field. Such nonlinear phenomena originate from the joint action of the lattice fluctuations and the reaction field. Under semiclassical approximation, it is found that the main effect of the reaction field is the renormalization of the Hamiltonian of interest. Its direct consequence is the two-step relaxation process: the spin is initially localized in a quasiequilibrium state, which is later

Detailed qualitative dynamic knowledge representation using a BioNetGen model of TLR-4 signaling and preconditioning.

PubMed

An, Gary C; Faeder, James R

2009-01-01

Intracellular signaling/synthetic pathways are being increasingly extensively characterized. However, while these pathways can be displayed in static diagrams, in reality they exist with a degree of dynamic complexity that is responsible for heterogeneous cellular behavior. Multiple parallel pathways exist and interact concurrently, limiting the ability to integrate the various identified mechanisms into a cohesive whole. Computational methods have been suggested as a means of concatenating this knowledge to aid in the understanding of overall system dynamics. Since the eventual goal of biomedical research is the identification and development of therapeutic modalities, computational representation must have sufficient detail to facilitate this 'engineering' process. Adding to the challenge, this type of representation must occur in a perpetual state of incomplete knowledge. We present a modeling approach to address this challenge that is both detailed and qualitative. This approach is termed 'dynamic knowledge representation,' and is intended to be an integrated component of the iterative cycle of scientific discovery. BioNetGen (BNG), a software platform for modeling intracellular signaling pathways, was used to model the toll-like receptor 4 (TLR-4) signal transduction cascade. The informational basis of the model was a series of reference papers on modulation of (TLR-4) signaling, and some specific primary research papers to aid in the characterization of specific mechanistic steps in the pathway. This model was detailed with respect to the components of the pathway represented, but qualitative with respect to the specific reaction coefficients utilized to execute the reactions. Responsiveness to simulated lipopolysaccharide (LPS) administration was measured by tumor necrosis factor (TNF) production. Simulation runs included evaluation of initial dose-dependent response to LPS administration at 10, 100, 1000 and 10,000, and a subsequent examination of

Nonlinear dynamics of cardiovascular ageing

PubMed Central

Shiogai, Y.; Stefanovska, A.; McClintock, P.V.E.

2010-01-01

The application of methods drawn from nonlinear and stochastic dynamics to the analysis of cardiovascular time series is reviewed, with particular reference to the identification of changes associated with ageing. The natural variability of the heart rate (HRV) is considered in detail, including the respiratory sinus arrhythmia (RSA) corresponding to modulation of the instantaneous cardiac frequency by the rhythm of respiration. HRV has been intensively studied using traditional spectral analyses, e.g. by Fourier transform or autoregressive methods, and, because of its complexity, has been used as a paradigm for testing several proposed new methods of complexity analysis. These methods are reviewed. The application of time–frequency methods to HRV is considered, including in particular the wavelet transform which can resolve the time-dependent spectral content of HRV. Attention is focused on the cardio-respiratory interaction by introduction of the respiratory frequency variability signal (RFV), which can be acquired simultaneously with HRV by use of a respiratory effort transducer. Current methods for the analysis of interacting oscillators are reviewed and applied to cardio-respiratory data, including those for the quantification of synchronization and direction of coupling. These reveal the effect of ageing on the cardio-respiratory interaction through changes in the mutual modulation of the instantaneous cardiac and respiratory frequencies. Analyses of blood flow signals recorded with laser Doppler flowmetry are reviewed and related to the current understanding of how endothelial-dependent oscillations evolve with age: the inner lining of the vessels (the endothelium) is shown to be of crucial importance to the emerging picture. It is concluded that analyses of the complex and nonlinear dynamics of the cardiovascular system can illuminate the mechanisms of blood circulation, and that the heart, the lungs and the vascular system function as a single entity in

Nonlinear dynamics of cardiovascular ageing

NASA Astrophysics Data System (ADS)

Shiogai, Y.; Stefanovska, A.; McClintock, P. V. E.

2010-03-01

The application of methods drawn from nonlinear and stochastic dynamics to the analysis of cardiovascular time series is reviewed, with particular reference to the identification of changes associated with ageing. The natural variability of the heart rate (HRV) is considered in detail, including the respiratory sinus arrhythmia (RSA) corresponding to modulation of the instantaneous cardiac frequency by the rhythm of respiration. HRV has been intensively studied using traditional spectral analyses, e.g. by Fourier transform or autoregressive methods, and, because of its complexity, has been used as a paradigm for testing several proposed new methods of complexity analysis. These methods are reviewed. The application of time-frequency methods to HRV is considered, including in particular the wavelet transform which can resolve the time-dependent spectral content of HRV. Attention is focused on the cardio-respiratory interaction by introduction of the respiratory frequency variability signal (RFV), which can be acquired simultaneously with HRV by use of a respiratory effort transducer. Current methods for the analysis of interacting oscillators are reviewed and applied to cardio-respiratory data, including those for the quantification of synchronization and direction of coupling. These reveal the effect of ageing on the cardio-respiratory interaction through changes in the mutual modulation of the instantaneous cardiac and respiratory frequencies. Analyses of blood flow signals recorded with laser Doppler flowmetry are reviewed and related to the current understanding of how endothelial-dependent oscillations evolve with age: the inner lining of the vessels (the endothelium) is shown to be of crucial importance to the emerging picture. It is concluded that analyses of the complex and nonlinear dynamics of the cardiovascular system can illuminate the mechanisms of blood circulation, and that the heart, the lungs and the vascular system function as a single entity in

Nanoscale organization and dynamics of the siglec CD22 cooperate with the cytoskeleton in restraining BCR signalling.

PubMed

Gasparrini, Francesca; Feest, Christoph; Bruckbauer, Andreas; Mattila, Pieta K; Müller, Jennifer; Nitschke, Lars; Bray, Dennis; Batista, Facundo D

2016-02-01

Receptor organization and dynamics at the cell membrane are important factors of signal transduction regulation. Using super-resolution microscopy and single-particle tracking, we show how the negative coreceptor CD22 works with the cortical cytoskeleton in restraining BCR signalling. In naïve B cells, we found endogenous CD22 to be highly mobile and organized into nanodomains. The landscape of CD22 and its lateral diffusion were perturbed either in the absence of CD45 or when the CD22 lectin domain was mutated. To understand how a relatively low number of CD22 molecules can keep BCR signalling in check, we generated Brownian dynamic simulations and supported them with ex vivo experiments. This combined approach suggests that the inhibitory function of CD22 is influenced by its nanoscale organization and is ensured by its fast diffusion enabling a "global BCR surveillance" at the plasma membrane. © 2015 The Authors.

ICESAT GLAS Altimetry Measurements: Received Signal Dynamic Range and Saturation Correction

NASA Technical Reports Server (NTRS)

Sun, Xiaoli; Abshire, James B.; Borsa, Adrian A.; Fricker, Helen Amanda; Yi, Donghui; Dimarzio, John P.; Paolo, Fernando S.; Brunt, Kelly M.; Harding, David J.; Neumann, Gregory A.

2017-01-01

NASAs Ice, Cloud, and land Elevation Satellite (ICESat), which operated between 2003 and 2009, made the first satellite-based global lidar measurement of earths ice sheet elevations, sea-ice thickness, and vegetation canopy structure. The primary instrument on ICESat was the Geoscience Laser Altimeter System (GLAS), which measured the distance from the spacecraft to the earth's surface via the roundtrip travel time of individual laser pulses. GLAS utilized pulsed lasers and a direct detection receiver consisting of a silicon avalanche photodiode and a waveform digitizer. Early in the mission, the peak power of the received signal from snow and ice surfaces was found to span a wider dynamic range than anticipated, often exceeding the linear dynamic range of the GLAS 1064-nm detector assembly. The resulting saturation of the receiver distorted the recorded signal and resulted in range biases as large as approximately 50 cm for ice- and snow-covered surfaces. We developed a correction for this saturation range bias based on laboratory tests using a spare flight detector, and refined the correction by comparing GLAS elevation estimates with those derived from Global Positioning System surveys over the calibration site at the salar de Uyuni, Bolivia. Applying the saturation correction largely eliminated the range bias due to receiver saturation for affected ICESat measurements over Uyuni and significantly reduced the discrepancies at orbit crossovers located on flat regions of the Antarctic ice sheet.

A Discrete Dynamical System Approach to Pathway Activation Profiles of Signaling Cascades.

PubMed

Catozzi, S; Sepulchre, J-A

2017-08-01

In living organisms, cascades of covalent modification cycles are one of the major intracellular signaling mechanisms, allowing to transduce physical or chemical stimuli of the external world into variations of activated biochemical species within the cell. In this paper, we develop a novel method to study the stimulus-response of signaling cascades and overall the concept of pathway activation profile which is, for a given stimulus, the sequence of activated proteins at each tier of the cascade. Our approach is based on a correspondence that we establish between the stationary states of a cascade and pieces of orbits of a 2D discrete dynamical system. The study of its possible phase portraits in function of the biochemical parameters, and in particular of the contraction/expansion properties around the fixed points of this discrete map, as well as their bifurcations, yields a classification of the cascade tiers into three main types, whose biological impact within a signaling network is examined. In particular, our approach enables to discuss quantitatively the notion of cascade amplification/attenuation from this new perspective. The method allows also to study the interplay between forward and "retroactive" signaling, i.e., the upstream influence of an inhibiting drug bound to the last tier of the cascade.

Analyses of the dynamic docking test system for advanced mission docking system test programs. [Apollo Soyuz Test Project

NASA Technical Reports Server (NTRS)

Gates, R. M.; Williams, J. E.

1974-01-01

Results are given of analytical studies performed in support of the design, implementation, checkout and use of NASA's dynamic docking test system (DDTS). Included are analyses of simulator components, a list of detailed operational test procedures, a summary of simulator performance, and an analysis and comparison of docking dynamics and loads obtained by test and analysis.

Hybrid learning in signalling games

NASA Astrophysics Data System (ADS)

Barrett, Jeffrey A.; Cochran, Calvin T.; Huttegger, Simon; Fujiwara, Naoki

2017-09-01

Lewis-Skyrms signalling games have been studied under a variety of low-rationality learning dynamics. Reinforcement dynamics are stable but slow and prone to evolving suboptimal signalling conventions. A low-inertia trial-and-error dynamical like win-stay/lose-randomise is fast and reliable at finding perfect signalling conventions but unstable in the context of noise or agent error. Here we consider a low-rationality hybrid of reinforcement and win-stay/lose-randomise learning that exhibits the virtues of both. This hybrid dynamics is reliable, stable and exceptionally fast.

Clustering in Cell Cycle Dynamics with General Response/Signaling Feedback

PubMed Central

Young, Todd R.; Fernandez, Bastien; Buckalew, Richard; Moses, Gregory; Boczko, Erik M.

2011-01-01

Motivated by experimental and theoretical work on autonomous oscillations in yeast, we analyze ordinary differential equations models of large populations of cells with cell-cycle dependent feedback. We assume a particular type of feedback that we call Responsive/Signaling (RS), but do not specify a functional form of the feedback. We study the dynamics and emergent behaviour of solutions, particularly temporal clustering and stability of clustered solutions. We establish the existence of certain periodic clustered solutions as well as “uniform” solutions and add to the evidence that cell-cycle dependent feedback robustly leads to cell-cycle clustering. We highlight the fundamental differences in dynamics between systems with negative and positive feedback. For positive feedback systems the most important mechanism seems to be the stability of individual isolated clusters. On the other hand we find that in negative feedback systems, clusters must interact with each other to reinforce coherence. We conclude from various details of the mathematical analysis that negative feedback is most consistent with observations in yeast experiments. PMID:22001733

Methods for removal of unwanted signals from gravity time-series: Comparison using linear techniques complemented with analysis of system dynamics

NASA Astrophysics Data System (ADS)

Valencio, Arthur; Grebogi, Celso; Baptista, Murilo S.

2017-10-01

The presence of undesirable dominating signals in geophysical experimental data is a challenge in many subfields. One remarkable example is surface gravimetry, where frequencies from Earth tides correspond to time-series fluctuations up to a thousand times larger than the phenomena of major interest, such as hydrological gravity effects or co-seismic gravity changes. This work discusses general methods for the removal of unwanted dominating signals by applying them to 8 long-period gravity time-series of the International Geodynamics and Earth Tides Service, equivalent to the acquisition from 8 instruments in 5 locations representative of the network. We compare three different conceptual approaches for tide removal: frequency filtering, physical modelling, and data-based modelling. Each approach reveals a different limitation to be considered depending on the intended application. Vestiges of tides remain in the residues for the modelling procedures, whereas the signal was distorted in different ways by the filtering and data-based procedures. The linear techniques employed were power spectral density, spectrogram, cross-correlation, and classical harmonics decomposition, while the system dynamics was analysed by state-space reconstruction and estimation of the largest Lyapunov exponent. Although the tides could not be completely eliminated, they were sufficiently reduced to allow observation of geophysical events of interest above the 10 nm s-2 level, exemplified by a hydrology-related event of 60 nm s-2. The implementations adopted for each conceptual approach are general, so that their principles could be applied to other kinds of data affected by undesired signals composed mainly by periodic or quasi-periodic components.

Increasing the Contrast-to-Noise Ratio of MRI Signals for Regional Assessment of Dynamic Cerebral Autoregulation.

PubMed

Jara, José L; Saeed, Nazia P; Panerai, Ronney B; Robinson, Thompson G

2018-01-01

To devise an appropriate measure of the quality of a magnetic resonance imaging (MRI) signal for the assessment of dynamic cerebral autoregulation, and propose simple strategies to improve its quality. Magnetic resonance images of 11 healthy subjects were scanned during a transient decrease in arterial blood pressure (BP). Mean signals were extracted from non-overlapping brain regions for each image. An ad-hoc contrast-to-noise ratio (CNR) was used to evaluate the quality of these regional signals. Global mean signals were obtained by averaging the set of regional signals resulting after applying a Hampel filter and discarding a proportion of the lower quality component signals. Significant improvements in CNR values of global mean signals were obtained, whilst maintaining significant correlation with the original ones. A Hampel filter with a small moving window and a low rejection threshold combined with a selection of the 50% component signals seems a recommendable option. This work has demonstrated the possibility of improving the quality of MRI signals acquired during transient drops in BP. This approach needs validation at a voxel level, which could help to consolidate MRI as a technological alternative to the standard techniques for the study of cerebral autoregulation.

Incentives in the family II: behavioral dynamics and the evolution of non-costly signaling.

PubMed

Akçay, Erol

2012-02-07

In many biological and social interactions, individuals with private information have incentives to misrepresent their information. A prominent example is when offspring know their need or condition but the parents do not. Theory showed that signal costs can ensure truthful communication in such situations, but further studies have cast in doubt whether empirically measured costs are high enough to sustain honesty, and whether the costly signaling equilibrium represents a fitness advantage over non-signaling. Here, I tackle these issues with a model of signaling that takes place at the behavioral time-scale through dynamic responses of individuals to each other. I then embed this behavioral model in an evolutionary one that asks how the decision rules of the parent and offspring evolve in response to the trade-off between signal costs and the costs of provisioning. I find that a non-costly honest signaling equilibrium can evolve when relatedness between siblings is above a certain threshold. This threshold is lower when (i) offspring get satiated more quickly, (ii) the cost of provisioning to the parent escalates less rapidly, or (iii) the variation in offspring need is higher. These results provide a potential resolution to the apparent paradox of costly begging. I also discuss the relation between costly signaling and mechanism design theories. Copyright © 2011 Elsevier Ltd. All rights reserved.

Advances in dynamic modeling of colorectal cancer signaling-network regions, a path toward targeted therapies

PubMed Central

Kolch, Walter; Kholodenko, Boris N.; Ambrosi, Cristina De; Barla, Annalisa; Biganzoli, Elia M.; Nencioni, Alessio; Patrone, Franco; Ballestrero, Alberto; Zoppoli, Gabriele; Verri, Alessandro; Parodi, Silvio

2015-01-01

The interconnected network of pathways downstream of the TGFβ, WNT and EGF-families of receptor ligands play an important role in colorectal cancer pathogenesis. We studied and implemented dynamic simulations of multiple downstream pathways and described the section of the signaling network considered as a Molecular Interaction Map (MIM). Our simulations used Ordinary Differential Equations (ODEs), which involved 447 reactants and their interactions. Starting from an initial “physiologic condition”, the model can be adapted to simulate individual pathologic cancer conditions implementing alterations/mutations in relevant onco-proteins. We verified some salient model predictions using the mutated colorectal cancer lines HCT116 and HT29. We measured the amount of MYC and CCND1 mRNAs and AKT and ERK phosphorylated proteins, in response to individual or combination onco-protein inhibitor treatments. Experimental and simulation results were well correlated. Recent independently published results were also predicted by our model. Even in the presence of an approximate and incomplete signaling network information, a predictive dynamic modeling seems already possible. An important long term road seems to be open and can be pursued further, by incremental steps, toward even larger and better parameterized MIMs. Personalized treatment strategies with rational associations of signaling-proteins inhibitors, could become a realistic goal. PMID:25671297

Dynamic Bayesian Network Modeling of the Interplay between EGFR and Hedgehog Signaling.

PubMed

Fröhlich, Holger; Bahamondez, Gloria; Götschel, Frank; Korf, Ulrike

2015-01-01

Aberrant activation of sonic Hegdehog (SHH) signaling has been found to disrupt cellular differentiation in many human cancers and to increase proliferation. The SHH pathway is known to cross-talk with EGFR dependent signaling. Recent studies experimentally addressed this interplay in Daoy cells, which are presumable a model system for medulloblastoma, a highly malignant brain tumor that predominately occurs in children. Currently ongoing are several clinical trials for different solid cancers, which are designed to validate the clinical benefits of targeting the SHH in combination with other pathways. This has motivated us to investigate interactions between EGFR and SHH dependent signaling in greater depth. To our knowledge, there is no mathematical model describing the interplay between EGFR and SHH dependent signaling in medulloblastoma so far. Here we come up with a fully probabilistic approach using Dynamic Bayesian Networks (DBNs). To build our model, we made use of literature based knowledge describing SHH and EGFR signaling and integrated gene expression (Illumina) and cellular location dependent time series protein expression data (Reverse Phase Protein Arrays). We validated our model by sub-sampling training data and making Bayesian predictions on the left out test data. Our predictions focusing on key transcription factors and p70S6K, showed a high level of concordance with experimental data. Furthermore, the stability of our model was tested by a parametric bootstrap approach. Stable network features were in agreement with published data. Altogether we believe that our model improved our understanding of the interplay between two highly oncogenic signaling pathways in Daoy cells. This may open new perspectives for the future therapy of Hedghog/EGF-dependent solid tumors.

Comparison of Dynamical Behaviors Between Monofunctional and Bifunctional Two-Component Signaling Modules

NASA Astrophysics Data System (ADS)

Yang, Xiyan; Wu, Yahao; Yuan, Zhanjiang

2015-06-01

Two-component signaling modules exist extensively in bacteria and microbes. These modules can be, based on their distinct network structures, divided into two types: the monofunctional system (denoted by MFS) where the sensor kinase (SK) modulates only phosphorylation of the response regulator (RR), and the bifunctional system (denoted by BFS) where the SK catalyzes both phosphorylation and dephosphorylation of the RR. Here, we analyze dynamical behaviors of these two systems based on stability theory, focusing on differences between them. The analysis of the deterministic behavior indicates that there is no difference between the two modules, that is, each system has the unique stable steady state. However, there are significant differences in stochastic behavior between them. Specifically, if the mean phosphorylated SK level is kept the same for the two modules, then the variance and the Fano factor for the phosphorylated RR in the BFS are always no less than those in the MFS, indicating that bifunctionality always enhances fluctuations. The correlation between the phosphorylated SK and the phosphorylated RR in the BFS is always positive mainly due to competition between system components, but this correlation in the MFS may be positive, almost zero, or negative, depending on the ratio between two rate constants. Our overall analysis indicates that differences between dynamical behaviors of monofunctional and bifunctional signaling modules are mainly in the stochastic rather than deterministic aspect.

Spatially uniform and nonuniform analyses of electroencephalographic dynamics,with application to the topography of the alpha rhythm

NASA Astrophysics Data System (ADS)

O'Connor, S. C.; Robinson, P. A.

2004-07-01

Corticothalamic dynamics are investigated using a model in which spatial nonuniformities are incorporated via the coupling of spatial eigenmodes. Comparison of spectra generated using the nonuniform analysis with those generated using a uniform one demonstrates that, for most frequencies, local activity is only weakly dependent on activity elsewhere in the cortex; however, dispersion of low-wave-number activity ensures that distant dynamics influence local dynamics at low frequencies (below approximately 2Hz ), and at the alpha frequency (approximately 10Hz ), where propagating signals are inherently weakly damped, and wavelengths are large. When certain model parameters have similar spatial profiles, as is expected from physiology, the low-frequency discrepancies tend to cancel, and the uniform analysis with local parameter values is an adequate approximation to the full nonuniform one across the whole spectrum, at least for large-scale nonuniformities. After comparing the uniform and nonuniform analyses, we consider one possible application of the nonuniform analysis: studying the phenomenon of occipital alpha dominance, whereby the alpha frequency and power are greater at the back of the head (occipitally) than at the front. In order to infer realistic nonuniformities in the model parameters, the uniform version of the model is first fitted to data recorded from 98 normal subjects in a waking, eyes-closed state. This yields a set of parameters at each of five electrode sites along the midline. The inferred parameter nonuniformities are consistent with anatomical and physiological constraints. Introducing these spatial profiles into the full nonuniform model then quantitatively reproduces observed site-dependent variations in the alpha power and frequency. The results confirm that the frequency shift is mainly due to a decrease in the corticothalamic propagation delay, but indicate that the delay nonuniformity cannot account for the observed occipital increase in

Structural Dynamic Analyses And Test Predictions For Spacecraft Structures With Non-Linearities

NASA Astrophysics Data System (ADS)

Vergniaud, Jean-Baptiste; Soula, Laurent; Newerla, Alfred

2012-07-01

The overall objective of the mechanical development and verification process is to ensure that the spacecraft structure is able to sustain the mechanical environments encountered during launch. In general the spacecraft structures are a-priori assumed to behave linear, i.e. the responses to a static load or dynamic excitation, respectively, will increase or decrease proportionally to the amplitude of the load or excitation induced. However, past experiences have shown that various non-linearities might exist in spacecraft structures and the consequences of their dynamic effects can significantly affect the development and verification process. Current processes are mainly adapted to linear spacecraft structure behaviour. No clear rules exist for dealing with major structure non-linearities. They are handled outside the process by individual analysis and margin policy, and analyses after tests to justify the CLA coverage. Non-linearities can primarily affect the current spacecraft development and verification process on two aspects. Prediction of flights loads by launcher/satellite coupled loads analyses (CLA): only linear satellite models are delivered for performing CLA and no well-established rules exist how to properly linearize a model when non- linearities are present. The potential impact of the linearization on the results of the CLA has not yet been properly analyzed. There are thus difficulties to assess that CLA results will cover actual flight levels. Management of satellite verification tests: the CLA results generated with a linear satellite FEM are assumed flight representative. If the internal non- linearities are present in the tested satellite then there might be difficulties to determine which input level must be passed to cover satellite internal loads. The non-linear behaviour can also disturb the shaker control, putting the satellite at risk by potentially imposing too high levels. This paper presents the results of a test campaign performed in

Knee Joint Vibration Signal Analysis with Matching Pursuit Decomposition and Dynamic Weighted Classifier Fusion

PubMed Central

Cai, Suxian; Yang, Shanshan; Zheng, Fang; Lu, Meng; Wu, Yunfeng; Krishnan, Sridhar

2013-01-01

Analysis of knee joint vibration (VAG) signals can provide quantitative indices for detection of knee joint pathology at an early stage. In addition to the statistical features developed in the related previous studies, we extracted two separable features, that is, the number of atoms derived from the wavelet matching pursuit decomposition and the number of significant signal turns detected with the fixed threshold in the time domain. To perform a better classification over the data set of 89 VAG signals, we applied a novel classifier fusion system based on the dynamic weighted fusion (DWF) method to ameliorate the classification performance. For comparison, a single leastsquares support vector machine (LS-SVM) and the Bagging ensemble were used for the classification task as well. The results in terms of overall accuracy in percentage and area under the receiver operating characteristic curve obtained with the DWF-based classifier fusion method reached 88.76% and 0.9515, respectively, which demonstrated the effectiveness and superiority of the DWF method with two distinct features for the VAG signal analysis. PMID:23573175

Why the soliton wavelet transform is useful for nonlinear dynamic phenomena

NASA Astrophysics Data System (ADS)

Szu, Harold H.

1992-10-01

If signal analyses were perfect without noise and clutters, then any transform can be equally chosen to represent the signal without any loss of information. However, if the analysis using Fourier transform (FT) happens to be a nonlinear dynamic phenomenon, the effect of nonlinearity must be postponed until a later time when a complicated mode-mode coupling is attempted without the assurance of any convergence. Alternatively, there exists a new paradigm of linear transforms called wavelet transform (WT) developed for French oil explorations. Such a WT enjoys the linear superposition principle, the computational efficiency, and the signal/noise ratio enhancement for a nonsinusoidal and nonstationary signal. Our extensions to a dynamic WT and furthermore to an adaptive WT are possible due to the fact that there exists a large set of square-integrable functions that are special solutions of the nonlinear dynamic medium and could be adopted for the WT. In order to analyze nonlinear dynamics phenomena in ocean, we are naturally led to the construction of a soliton mother wavelet. This common sense of 'pay the nonlinear price now and enjoy the linearity later' is certainly useful to probe any nonlinear dynamics. Research directions in wavelets, such as adaptivity, and neural network implementations are indicated, e.g., tailoring an active sonar profile for explorations.

Integrated dynamic analysis simulation of space stations with controllable solar arrays (supplemental data and analyses)

NASA Technical Reports Server (NTRS)

Heinrichs, J. A.; Fee, J. J.

1972-01-01

Space station and solar array data and the analyses which were performed in support of the integrated dynamic analysis study. The analysis methods and the formulated digital simulation were developed. Control systems for space station altitude control and solar array orientation control include generic type control systems. These systems have been digitally coded and included in the simulation.

Dynamic mobility applications policy analysis : policy and institutional issues for multi-modal intelligent traffic signal system (MMITSS).

DOT National Transportation Integrated Search

2015-03-01

The Connected Vehicle Mobility Policy team (herein, policy team) developed this report to document policy considerations for the Multi-Modal Intelligent Traffic Signal System, or MMITSS. MMITSS comprises a bundle of dynamic mobility application...

A toolbox for discrete modelling of cell signalling dynamics.

PubMed

Paterson, Yasmin Z; Shorthouse, David; Pleijzier, Markus W; Piterman, Nir; Bendtsen, Claus; Hall, Benjamin A; Fisher, Jasmin

2018-06-18

In an age where the volume of data regarding biological systems exceeds our ability to analyse it, many researchers are looking towards systems biology and computational modelling to help unravel the complexities of gene and protein regulatory networks. In particular, the use of discrete modelling allows generation of signalling networks in the absence of full quantitative descriptions of systems, which are necessary for ordinary differential equation (ODE) models. In order to make such techniques more accessible to mainstream researchers, tools such as the BioModelAnalyzer (BMA) have been developed to provide a user-friendly graphical interface for discrete modelling of biological systems. Here we use the BMA to build a library of discrete target functions of known canonical molecular interactions, translated from ordinary differential equations (ODEs). We then show that these BMA target functions can be used to reconstruct complex networks, which can correctly predict many known genetic perturbations. This new library supports the accessibility ethos behind the creation of BMA, providing a toolbox for the construction of complex cell signalling models without the need for extensive experience in computer programming or mathematical modelling, and allows for construction and simulation of complex biological systems with only small amounts of quantitative data.

Elementary signaling modes predict the essentiality of signal transduction network components

PubMed Central

2011-01-01

Background Understanding how signals propagate through signaling pathways and networks is a central goal in systems biology. Quantitative dynamic models help to achieve this understanding, but are difficult to construct and validate because of the scarcity of known mechanistic details and kinetic parameters. Structural and qualitative analysis is emerging as a feasible and useful alternative for interpreting signal transduction. Results In this work, we present an integrative computational method for evaluating the essentiality of components in signaling networks. This approach expands an existing signaling network to a richer representation that incorporates the positive or negative nature of interactions and the synergistic behaviors among multiple components. Our method simulates both knockout and constitutive activation of components as node disruptions, and takes into account the possible cascading effects of a node's disruption. We introduce the concept of elementary signaling mode (ESM), as the minimal set of nodes that can perform signal transduction independently. Our method ranks the importance of signaling components by the effects of their perturbation on the ESMs of the network. Validation on several signaling networks describing the immune response of mammals to bacteria, guard cell abscisic acid signaling in plants, and T cell receptor signaling shows that this method can effectively uncover the essentiality of components mediating a signal transduction process and results in strong agreement with the results of Boolean (logical) dynamic models and experimental observations. Conclusions This integrative method is an efficient procedure for exploratory analysis of large signaling and regulatory networks where dynamic modeling or experimental tests are impractical. Its results serve as testable predictions, provide insights into signal transduction and regulatory mechanisms and can guide targeted computational or experimental follow-up studies. The

Dynamic ubiquitin signaling in cell cycle regulation

PubMed Central

Gilberto, Samuel

2017-01-01

The cell division cycle is driven by a collection of enzymes that coordinate DNA duplication and separation, ensuring that genomic information is faithfully and perpetually maintained. The activity of the effector proteins that perform and coordinate these biological processes oscillates by regulated expression and/or posttranslational modifications. Ubiquitylation is a cardinal cellular modification and is long known for driving cell cycle transitions. In this review, we emphasize emerging concepts of how ubiquitylation brings the necessary dynamicity and plasticity that underlie the processes of DNA replication and mitosis. New studies, often focusing on the regulation of chromosomal proteins like DNA polymerases or kinetochore kinases, are demonstrating that ubiquitylation is a versatile modification that can be used to fine-tune these cell cycle events, frequently through processes that do not involve proteasomal degradation. Understanding how the increasing variety of identified ubiquitin signals are transduced will allow us to develop a deeper mechanistic perception of how the multiple factors come together to faithfully propagate genomic information. Here, we discuss these and additional conceptual challenges that are currently under study toward understanding how ubiquitin governs cell cycle regulation. PMID:28684425

Dynamic ubiquitin signaling in cell cycle regulation.

PubMed

Gilberto, Samuel; Peter, Matthias

2017-08-07

The cell division cycle is driven by a collection of enzymes that coordinate DNA duplication and separation, ensuring that genomic information is faithfully and perpetually maintained. The activity of the effector proteins that perform and coordinate these biological processes oscillates by regulated expression and/or posttranslational modifications. Ubiquitylation is a cardinal cellular modification and is long known for driving cell cycle transitions. In this review, we emphasize emerging concepts of how ubiquitylation brings the necessary dynamicity and plasticity that underlie the processes of DNA replication and mitosis. New studies, often focusing on the regulation of chromosomal proteins like DNA polymerases or kinetochore kinases, are demonstrating that ubiquitylation is a versatile modification that can be used to fine-tune these cell cycle events, frequently through processes that do not involve proteasomal degradation. Understanding how the increasing variety of identified ubiquitin signals are transduced will allow us to develop a deeper mechanistic perception of how the multiple factors come together to faithfully propagate genomic information. Here, we discuss these and additional conceptual challenges that are currently under study toward understanding how ubiquitin governs cell cycle regulation. © 2017 Gilberto and Peter.

The impact of global signal regression on resting state correlations: Are anti-correlated networks introduced?

PubMed Central

Murphy, Kevin; Birn, Rasmus M.; Handwerker, Daniel A.; Jones, Tyler B.; Bandettini, Peter A.

2009-01-01

Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step. PMID:18976716

The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?

PubMed

Murphy, Kevin; Birn, Rasmus M; Handwerker, Daniel A; Jones, Tyler B; Bandettini, Peter A

2009-02-01

Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step.

Variational Assimilation of Global Microwave Rainfall Retrievals: Physical and Dynamical Impact on GEOS Analyses and Forecasts

NASA Technical Reports Server (NTRS)

Lin, Xin; Zhang, Sara Q.; Hou, Arthur Y.

2006-01-01

Global microwave rainfall retrievals from a 5-satellite constellation, including TMI from TRMM, SSWI from DMSP F13, F14 and F15, and AMSR-E from EOS-AQUA, are assimilated into the NASA Goddard Earth Observing System (GEOS) Data Assimilation System (DAS) using a 1-D variational continuous assimilation (VCA) algorithm. The physical and dynamical impact of rainfall assimilation on GEOS analyses and forecasts is examined at various temporal and spatial scales. This study demonstrates that the 1-D VCA algorithm, which was originally developed and evaluated for rainfall assimilations over tropical oceans, can effectively assimilate satellite microwave rainfall retrievals and improve GEOS analyses over both the Tropics and the extratropics where the atmospheric processes are dominated by different large-scale dynamics and moist physics, and also over the land, where rainfall estimates from passive microwave radiometers are believed to be less accurate. Results show that rainfall assimilation renders the GEOS analysis physically and dynamically more consistent with the observed precipitation at the monthly-mean and 6-hour time scales. Over regions where the model precipitation tends to misbehave in distinctly different rainy regimes, the 1-D VCA algorithm, by compensating for errors in the model s moist time-tendency in a 6-h analysis window, is able to bring the rainfall analysis closer to the observed. The radiation and cloud fields also tend to be in better agreement with independent satellite observations in the rainfall-assimilation m especially over regions where rainfall analyses indicate large improvements. Assimilation experiments with and without rainfall data for a midlatitude frontal system clearly indicates that the GEOS analysis is improved through changes in the thermodynamic and dynamic fields that respond to the rainfall assimilation. The synoptic structures of temperature, moisture, winds, divergence, and vertical motion, as well as vorticity are more

Sequence and structural analyses of nuclear export signals in the NESdb database

PubMed Central

Xu, Darui; Farmer, Alicia; Collett, Garen; Grishin, Nick V.; Chook, Yuh Min

2012-01-01

We compiled >200 nuclear export signal (NES)–containing CRM1 cargoes in a database named NESdb. We analyzed the sequences and three-dimensional structures of natural, experimentally identified NESs and of false-positive NESs that were generated from the database in order to identify properties that might distinguish the two groups of sequences. Analyses of amino acid frequencies, sequence logos, and agreement with existing NES consensus sequences revealed strong preferences for the Φ1-X3-Φ2-X2-Φ3-X-Φ4 pattern and for negatively charged amino acids in the nonhydrophobic positions of experimentally identified NESs but not of false positives. Strong preferences against certain hydrophobic amino acids in the hydrophobic positions were also revealed. These findings led to a new and more precise NES consensus. More important, three-dimensional structures are now available for 68 NESs within 56 different cargo proteins. Analyses of these structures showed that experimentally identified NESs are more likely than the false positives to adopt α-helical conformations that transition to loops at their C-termini and more likely to be surface accessible within their protein domains or be present in disordered or unobserved parts of the structures. Such distinguishing features for real NESs might be useful in future NES prediction efforts. Finally, we also tested CRM1-binding of 40 NESs that were found in the 56 structures. We found that 16 of the NES peptides did not bind CRM1, hence illustrating how NESs are easily misidentified. PMID:22833565

Dynamic generation of concentration- and temporal-dependent chemical signals in an integrated microfluidic device for single-cell analysis.

PubMed

Gonzalez-Suarez, Alan Mauricio; Peña-Del Castillo, Johanna G; Hernandez-Cruz, Arturo; Garcia-Cordero, Jose Luis

2018-06-19

Intracellular signaling pathways are affected by the temporal nature of external chemical signaling molecules such as neuro-transmitters or hormones. Developing high-throughput technologies to mimic these time-varying chemical signals and to analyze the response of single cells would deepen our understanding of signaling networks. In this work, we introduce a microfluidic platform to stimulate hundreds of single cells with chemical waveforms of tunable frequency and amplitude. Our device produces a linear gradient of 9 concentrations that are delivered to an equal number of chambers, each containing 492 microwells, where individual cells are captured. The device can alternate between the different stimuli concentrations and a control buffer, with a maximum operating frequency of 33 mHz that can be adjusted from a computer. Fluorescent time-lapse microscopy enables to obtain hundreds of thousands of data points from one experiment. We characterized the gradient performance and stability by staining hundreds of cells with calcein AM. We also assessed the capacity of our device to introduce periodic chemical stimuli of different amplitudes and frequencies. To demonstrate our device performance, we studied the dynamics of intracellular Ca2+ release from intracellular stores of HEK cells when stimulated with carbachol at 4.5 and 20 mHz. Our work opens the possibility of characterizing the dynamic responses in real time of signaling molecules to time-varying chemical stimuli with single cell resolution.

MO-F-CAMPUS-J-03: Sorting 2D Dynamic MR Images Using Internal Respiratory Signal for 4D MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wen, Z; Hui, C; Beddar, S

Purpose: To develop a novel algorithm to extract internal respiratory signal (IRS) for sorting dynamic magnetic resonance (MR) images in order to achieve four-dimensional (4D) MR imaging. Methods: Dynamic MR images were obtained with the balanced steady state free precession by acquiring each two-dimensional sagittal slice repeatedly for more than one breathing cycle. To generate a robust IRS, we used 5 different representative internal respiratory surrogates in both the image space (body area) and the Fourier space (the first two low-frequency phase components in the anterior-posterior direction, and the first two low-frequency phase components in the superior-inferior direction). A clusteringmore » algorithm was then used to search for a group of similar individual internal signals, which was then used to formulate the final IRS. A phantom study and a volunteer study were performed to demonstrate the effectiveness of this algorithm. The IRS was compared to the signal from the respiratory bellows. Results: The IRS computed by our algorithm matched well with the bellows signal in both the phantom and the volunteer studies. On average, the normalized cross correlation between the IRS and the bellows signal was 0.97 in the phantom study and 0.87 in the volunteer study, respectively. The average difference between the end inspiration times in the IRS and bellows signal was 0.18 s in the phantom study and 0.14 s in the volunteer study, respectively. 4D images sorted based on the IRS showed minimal mismatched artifacts, and the motion of the anatomy was coherent with the respiratory phases. Conclusion: A novel algorithm was developed to generate IRS from dynamic MR images to achieve 4D MR imaging. The performance of the IRS was comparable to that of the bellows signal. It can be easily implemented into the clinic and potentially could replace the use of external respiratory surrogates. This research was partially funded by the the Center for Radiation Oncology

Stream restoration in dynamic fluvial systems: Scientific approaches, analyses, and tools

NASA Astrophysics Data System (ADS)

Schultz, Colin

2012-04-01

In the United States the average annual investment in river restoration programs is approximately $1 billion. Despite this burgeoning industry, the National Water Quality Inventory, which tracks the health of the nation's rivers, has shown no serious improvement in cumulative river health since the early 1990s. In the AGU monographStream Restoration in Dynamic Fluvial Systems: Scientific Approaches, Analyses, and Tools, editors Andrew Simon, Sean J. Bennett, and Janine M. Castro pull together the latest evidence-based understanding of stream restoration practices, with an aim of guiding the further development of the field and helping to right its apparently unsuccessful course. In this interview, Eos talks to Sean J. Bennett, University of Buffalo, about the culture, practice, and promise of restoring rivers.

Dynamic models to analyse the influence of the seat belt in a frontal collision

NASA Astrophysics Data System (ADS)

Oana, Oţăt; Nicolae, Dumitru; Ilie, Dumitru

2017-10-01

Traffic accidents are influenced by various factors, yet, the highest impacting ones are related to vehicle impact speed and collision type. Also, passive vehicle safety systems play a significant role upon the injuries suffered by vehicle occupants. Under the circumstances, a particularly important aspect to consider when using such systems is the position of the vehicle’s driver and its occupants. In what follows we embark upon an in-depth analysis in order to investigate the contact effects between the seat belt and the driver, under a dynamic regime. We set out to identify the variation of the kinematic and dynamic parameters for both the driver and the seat belt via comparative analyses between the normal position of the driver and some other out of position instances, considered as critical.

Dynamic Receptor Team Formation Can Explain the High Signal Transduction Gain in Escherichia coli

NASA Astrophysics Data System (ADS)

Albert, R.; Chiu, Y.; Othmer, H.

2004-05-01

Evolution has provided many organisms with sophisticated sensory systems that enable them to respond to signals in their environment. The response frequently involves alteration in the pattern of movement, such as the chemokinesis of the bacterium Escherichia coli, which swims by rotating its flagella. When rotated counterclockwise (CCW) the flagella coalesce into a propulsive bundle, producing a relatively straight ``run'', and when rotated clockwise (CW) they fly apart, resulting in a ``tumble'' which reorients the cell with little translocation. A stochastic process generates the runs and tumbles, and in a chemoeffector gradient runs that carry the cell in a favorable direction are extended. The overall structure of the signal transduction pathways is well-characterized in E. coli, but important details are still not understood. Only recently has a source of gain in the signal transduction network been identified experimentally, and here we present a mathematical model based on dynamic assembly of receptor teams that can explain this observation.

Aurora A drives early signalling and vesicle dynamics during T-cell activation

PubMed Central

Blas-Rus, Noelia; Bustos-Morán, Eugenio; Pérez de Castro, Ignacio; de Cárcer, Guillermo; Borroto, Aldo; Camafeita, Emilio; Jorge, Inmaculada; Vázquez, Jesús; Alarcón, Balbino; Malumbres, Marcos; Martín-Cófreces, Noa B.; Sánchez-Madrid, Francisco

2016-01-01

Aurora A is a serine/threonine kinase that contributes to the progression of mitosis by inducing microtubule nucleation. Here we have identified an unexpected role for Aurora A kinase in antigen-driven T-cell activation. We find that Aurora A is phosphorylated at the immunological synapse (IS) during TCR-driven cell contact. Inhibition of Aurora A with pharmacological agents or genetic deletion in human or mouse T cells severely disrupts the dynamics of microtubules and CD3ζ-bearing vesicles at the IS. The absence of Aurora A activity also impairs the activation of early signalling molecules downstream of the TCR and the expression of IL-2, CD25 and CD69. Aurora A inhibition causes delocalized clustering of Lck at the IS and decreases phosphorylation levels of tyrosine kinase Lck, thus indicating Aurora A is required for maintaining Lck active. These findings implicate Aurora A in the propagation of the TCR activation signal. PMID:27091106

Quantification of Interactions between Dynamic Cellular Network Functionalities by Cascaded Layering

PubMed Central

Prescott, Thomas P.; Lang, Moritz; Papachristodoulou, Antonis

2015-01-01

Large, naturally evolved biomolecular networks typically fulfil multiple functions. When modelling or redesigning such systems, functional subsystems are often analysed independently first, before subsequent integration into larger-scale computational models. In the design and analysis process, it is therefore important to quantitatively analyse and predict the dynamics of the interactions between integrated subsystems; in particular, how the incremental effect of integrating a subsystem into a network depends on the existing dynamics of that network. In this paper we present a framework for simulating the contribution of any given functional subsystem when integrated together with one or more other subsystems. This is achieved through a cascaded layering of a network into functional subsystems, where each layer is defined by an appropriate subset of the reactions. We exploit symmetries in our formulation to exhaustively quantify each subsystem’s incremental effects with minimal computational effort. When combining subsystems, their isolated behaviour may be amplified, attenuated, or be subject to more complicated effects. We propose the concept of mutual dynamics to quantify such nonlinear phenomena, thereby defining the incompatibility and cooperativity between all pairs of subsystems when integrated into any larger network. We exemplify our theoretical framework by analysing diverse behaviours in three dynamic models of signalling and metabolic pathways: the effect of crosstalk mechanisms on the dynamics of parallel signal transduction pathways; reciprocal side-effects between several integral feedback mechanisms and the subsystems they stabilise; and consequences of nonlinear interactions between elementary flux modes in glycolysis for metabolic engineering strategies. Our analysis shows that it is not sufficient to just specify subsystems and analyse their pairwise interactions; the environment in which the interaction takes place must also be explicitly

Balanced ionotropic receptor dynamics support signal estimation via voltage-dependent membrane noise.

PubMed

Marcoux, Curtis M; Clarke, Stephen E; Nesse, William H; Longtin, Andre; Maler, Leonard

2016-01-01

Encoding behaviorally relevant stimuli in a noisy background is critical for animals to survive in their natural environment. We identify core biophysical and synaptic mechanisms that permit the encoding of low-frequency signals in pyramidal neurons of the weakly electric fish Apteronotus leptorhynchus, an animal that can accurately encode even miniscule amplitude modulations of its self-generated electric field. We demonstrate that slow NMDA receptor (NMDA-R)-mediated excitatory postsynaptic potentials (EPSPs) are able to summate over many interspike intervals (ISIs) of the primary electrosensory afferents (EAs), effectively eliminating the baseline EA ISI correlations from the pyramidal cell input. Together with a dynamic balance of NMDA-R and GABA-A-R currents, this permits stimulus-evoked changes in EA spiking to be transmitted efficiently to target electrosensory lobe (ELL) pyramidal cells, for encoding low-frequency signals. Interestingly, AMPA-R activity is depressed and appears to play a negligible role in the generation of action potentials. Instead, we hypothesize that cell-intrinsic voltage-dependent membrane noise supports the encoding of perithreshold sensory input; this noise drives a significant proportion of pyramidal cell spikes. Together, these mechanisms may be sufficient for the ELL to encode signals near the threshold of behavioral detection. Copyright © 2016 the American Physiological Society.

Enhancing Observability of Signal Composition and Error Signatures During Dynamic SEE Analog to Digital Device Testing

NASA Technical Reports Server (NTRS)

Berg, M.; Buchner, S.; Kim, H.; Friendlich, M.; Perez, C.; Phan, A.; Seidleck, C.; LaBel, K.; Kruckmeyer, K.

2010-01-01

A novel approach to dynamic SEE ADC testing is presented. The benefits of this test scheme versus prior implemented techniques include the ability to observe ADC SEE errors that are in the form of phase shifts, single bit upsets, bursts of disrupted signal composition, and device clock loss.

Analysing 21cm signal with artificial neural network

NASA Astrophysics Data System (ADS)

Shimabukuro, Hayato; a Semelin, Benoit

2018-05-01

The 21cm signal at epoch of reionization (EoR) should be observed within next decade. We expect that cosmic 21cm signal at the EoR provides us both cosmological and astrophysical information. In order to extract fruitful information from observation data, we need to develop inversion method. For such a method, we introduce artificial neural network (ANN) which is one of the machine learning techniques. We apply the ANN to inversion problem to constrain astrophysical parameters from 21cm power spectrum. We train the architecture of the neural network with 70 training datasets and apply it to 54 test datasets with different value of parameters. We find that the quality of the parameter reconstruction depends on the sensitivity of the power spectrum to the different parameter sets at a given redshift and also find that the accuracy of reconstruction is improved by increasing the number of given redshifts. We conclude that the ANN is viable inversion method whose main strength is that they require a sparse extrapolation of the parameter space and thus should be usable with full simulation.

Combined analytical and numerical approaches in Dynamic Stability analyses of engineering systems

NASA Astrophysics Data System (ADS)

Náprstek, Jiří

2015-03-01

Dynamic Stability is a widely studied area that has attracted many researchers from various disciplines. Although Dynamic Stability is usually associated with mechanics, theoretical physics or other natural and technical disciplines, it is also relevant to social, economic, and philosophical areas of our lives. Therefore, it is useful to occasionally highlight the general aspects of this amazing area, to present some relevant examples and to evaluate its position among the various branches of Rational Mechanics. From this perspective, the aim of this study is to present a brief review concerning the Dynamic Stability problem, its basic definitions and principles, important phenomena, research motivations and applications in engineering. The relationships with relevant systems that are prone to stability loss (encountered in other areas such as physics, other natural sciences and engineering) are also noted. The theoretical background, which is applicable to many disciplines, is presented. In this paper, the most frequently used Dynamic Stability analysis methods are presented in relation to individual dynamic systems that are widely discussed in various engineering branches. In particular, the Lyapunov function and exponent procedures, Routh-Hurwitz, Liénard, and other theorems are outlined together with demonstrations. The possibilities for analytical and numerical procedures are mentioned together with possible feedback from experimental research and testing. The strengths and shortcomings of these approaches are evaluated together with examples of their effective complementing of each other. The systems that are widely encountered in engineering are presented in the form of mathematical models. The analyses of their Dynamic Stability and post-critical behaviour are also presented. The stability limits, bifurcation points, quasi-periodic response processes and chaotic regimes are discussed. The limit cycle existence and stability are examined together with their

Time-Frequency Distribution Analyses of Ku-Band Radar Doppler Echo Signals

NASA Astrophysics Data System (ADS)

Bujaković, Dimitrije; Andrić, Milenko; Bondžulić, Boban; Mitrović, Srđan; Simić, Slobodan

2015-03-01

Real radar echo signals of a pedestrian, vehicle and group of helicopters are analyzed in order to maximize signal energy around central Doppler frequency in time-frequency plane. An optimization, preserving this concentration, is suggested based on three well-known concentration measures. Various window functions and time-frequency distributions were optimization inputs. Conducted experiments on an analytic and three real signals have shown that energy concentration significantly depends on used time-frequency distribution and window function, for all three used criteria.

Vowel selection and its effects on perturbation and nonlinear dynamic measures.

PubMed

Maccallum, Julia K; Zhang, Yu; Jiang, Jack J

2011-01-01

Acoustic analysis of voice is typically conducted on recordings of sustained vowel phonation. This study applied perturbation and nonlinear dynamic analyses to the vowels /a/, /i/, and /u/ in order to determine vowel selection effects on analysis. Forty subjects (20 males and 20 females) with normal voices participated in recording. Traditional parameters of fundamental frequency, signal-to-noise ratio, percent jitter, and percent shimmer were calculated for the signals using CSpeech. Nonlinear dynamic parameters of correlation dimension and second-order entropy were also calculated. Perturbation analysis results were largely incongruous in this study and in previous research. Fundamental frequency results corroborated previous work, indicating higher fundamental frequency for /i/ and /u/ and lower fundamental frequency for /a/. Signal-to-noise ratio results showed that /i/ and /u/ have greater harmonic levels than /a/. Results of nonlinear dynamic analysis suggested that more complex activity may be evident in /a/ than in /i/ or /u/. Percent jitter and percent shimmer may not be useful for description of acoustic differences between vowels. Fundamental frequency, signal-to-noise ratio, and nonlinear dynamic parameters may be applied to characterize /a/ as having lower frequency, higher noise, and greater nonlinear components than /i/ and /u/. Copyright © 2010 S. Karger AG, Basel.

Conformational transition in signal transduction: metastable states and transition pathways in the activation of a signaling protein.

PubMed

Banerjee, Rahul; Yan, Honggao; Cukier, Robert I

2015-06-04

Signal transduction is of vital importance to the growth and adaptation of living organisms. The key to understand mechanisms of biological signal transduction is elucidation of the conformational dynamics of its signaling proteins, as the activation of a signaling protein is fundamentally a process of conformational transition from an inactive to an active state. A predominant form of signal transduction for bacterial sensing of environmental changes in the wild or inside their hosts is a variety of two-component systems, in which the conformational transition of a response regulator (RR) from an inactive to an active state initiates responses to the environmental changes. Here, RR activation has been investigated using RR468 as a model system by extensive unbiased all-atom molecular dynamics (MD) simulations in explicit solvent, starting from snapshots along a targeted MD trajectory that covers the conformational transition. Markov state modeling, transition path theory, and geometric analyses of the wealth of the MD data have provided a comprehensive description of the RR activation. It involves a network of metastable states, with one metastable state essentially the same as the inactive state and another very similar to the active state that are connected via a small set of intermediates. Five major pathways account for >75% of the fluxes of the conformational transition from the inactive to the active-like state. The thermodynamic stability of the states and the activation barriers between states are found, to identify rate-limiting steps. The conformal transition is initiated predominantly by movements of the β3α3 loop, followed by movements of the β4α4-loop and neighboring α4 helix region, and capped by additional movements of the β3α3 loop. A number of transient hydrophobic and hydrogen bond interactions are revealed, and they may be important for the conformational transition.

Investigation of Rhodopsin Dynamics in its Signaling State by Solid-State Deuterium NMR Spectroscopy

PubMed Central

Struts, Andrey V.; Chawla, Udeep; Perera, Suchithranga M.D.C.; Brown, Michael F.

2017-01-01

Site-directed deuterium NMR spectroscopy is a valuable tool to study the structural dynamics of biomolecules in cases where solution NMR is inapplicable. Solid-state 2H NMR spectral studies of aligned membrane samples of rhodopsin with selectively labeled retinal provide information on structural changes of the chromophore in different protein states. In addition, solid-state 2H NMR relaxation time measurements allow one to study the dynamics of the ligand during the transition from the inactive to the active state. Here we describe the methodological aspects of solid-state 2H NMR spectroscopy for functional studies of rhodopsin, with an emphasis on the dynamics of the retinal cofactor. We provide complete protocols for the preparation of NMR samples of rhodopsin with 11-cis-retinal selectively deuterated at the methyl groups in aligned membranes. In addition, we review optimized conditions for trapping the rhodopsin photointermediates; and lastly we address the challenging problem of trapping the signaling state of rhodopsin in aligned membrane films. PMID:25697522

Identity-by-descent analyses for measuring population dynamics and selection in recombining pathogens.

PubMed

Henden, Lyndal; Lee, Stuart; Mueller, Ivo; Barry, Alyssa; Bahlo, Melanie

2018-05-01

Identification of genomic regions that are identical by descent (IBD) has proven useful for human genetic studies where analyses have led to the discovery of familial relatedness and fine-mapping of disease critical regions. Unfortunately however, IBD analyses have been underutilized in analysis of other organisms, including human pathogens. This is in part due to the lack of statistical methodologies for non-diploid genomes in addition to the added complexity of multiclonal infections. As such, we have developed an IBD methodology, called isoRelate, for analysis of haploid recombining microorganisms in the presence of multiclonal infections. Using the inferred IBD status at genomic locations, we have also developed a novel statistic for identifying loci under positive selection and propose relatedness networks as a means of exploring shared haplotypes within populations. We evaluate the performance of our methodologies for detecting IBD and selection, including comparisons with existing tools, then perform an exploratory analysis of whole genome sequencing data from a global Plasmodium falciparum dataset of more than 2500 genomes. This analysis identifies Southeast Asia as having many highly related isolates, possibly as a result of both reduced transmission from intensified control efforts and population bottlenecks following the emergence of antimalarial drug resistance. Many signals of selection are also identified, most of which overlap genes that are known to be associated with drug resistance, in addition to two novel signals observed in multiple countries that have yet to be explored in detail. Additionally, we investigate relatedness networks over the selected loci and determine that one of these sweeps has spread between continents while the other has arisen independently in different countries. IBD analysis of microorganisms using isoRelate can be used for exploring population structure, positive selection and haplotype distributions, and will be a

Characterization of granular flow dynamics from the generated high-frequency seismic signal: insights from laboratory experiments

NASA Astrophysics Data System (ADS)

Mangeney, A.; Farin, M.; de Rosny, J.; Toussaint, R.; Trinh, P. T.

2017-12-01

Landslides, rock avalanche and rockfalls represent a major natural hazard in steep environments. However, owing to the lack of visual observations, the dynamics of these gravitational events is still not well understood. A burning challenge is to deduce the landslide dynamics (flow potential energy, involved volume, particle size…) from the characteristics of the generated seismic signal (radiated seismic energy, maximum amplitude, frequencies,...). Laboratory experiments of granular columns collapse are conducted on an inclined plane. The seismic signal generated by the collapse is recorded by piezoelectric accelerometers sensitive in a wide frequency range (1 Hz - 56 kHz). The granular flow are constituted with steel beads of same diameter. We compare the dynamic parameters of the granular flows, deduced from the movie of the experiments, to the seismic parameters deduced from the measured seismic signals. The ratio of radiated seismic energy to potential energy lost is shown to slightly decrease with slope angle and is between 0.2% and 9%. It decreases as time, slope angle and flow volume increase and when the particle diameter decreases. These results explain the dispersion over several orders of magnitude of the seismic efficiency of natural landslides. We distinguish two successive phases of rise and decay in the time profiles if the amplitude of the seismic signal and of the mean frequency of the signal generated by the granular flows. The rise phase and the maximum are shown to be independent of the slope angle. The maximum seismic amplitude coincides with the maximum flow speed in the direction normal to the slope but not with the maximum downslope speed. We observe that the shape of the seismic envelope and frequencies as a function of time changes after a critical slope angle, between 10° and 15° with respect to the horizontal, with a decay phase lasting much longer as slope angle increases, due to a change in the flow regime, from a dense to a more

On signals of phase transitions in salmon population dynamics

PubMed Central

Krkošek, Martin; Drake, John M.

2014-01-01

Critical slowing down (CSD) reflects the decline in resilience of equilibria near a bifurcation and may reveal early warning signals (EWS) of ecological phase transitions. We studied CSD in the recruitment dynamics of 120 stocks of three Pacific salmon (Oncorhynchus spp.) species in relation to critical transitions in fishery models. Pink salmon (Oncorhynchus gorbuscha) exhibited increased variability and autocorrelation in populations that had a growth parameter, r, close to zero, consistent with EWS of extinction. However, models and data for sockeye salmon (Oncorhynchus nerka) indicate that portfolio effects from heterogeneity in age-at-maturity may obscure EWS. Chum salmon (Oncorhynchus keta) show intermediate results. The data do not reveal EWS of Ricker-type bifurcations that cause oscillations and chaos at high r. These results not only provide empirical support for CSD in some ecological systems, but also indicate that portfolio effects of age structure may conceal EWS of some critical transitions. PMID:24759855

Observation of Wetland Dynamics with Global Navigation Satellite Signals Reflectometry

NASA Astrophysics Data System (ADS)

Zuffada, C.; Shah, R.; Nghiem, S. V.; Cardellach, E.; Chew, C. C.

2015-12-01

Wetland dynamics is crucial to changes in both atmospheric methane and terrestrial water storage. The Intergovernmental Panel on Climate Change's Fifth Assessment Report (IPCC AR5) highlights the role of wetlands as a key driver of methane (CH4) emission, which is more than one order of magnitude stronger than carbon dioxide as a greenhouse gas in the centennial time scale. Among the multitude of methane emission sources (hydrates, livestock, rice cultivation, freshwaters, landfills and waste, fossil fuels, biomass burning, termites, geological sources, and soil oxidation), wetlands constitute the largest contributor with the widest uncertainty range of 177-284 Tg(CH4) yr-1 according to the IPCC estimate. Wetlands are highly susceptible to climate change that might lead to wetland collapse. Such wetland destruction would decrease the terrestrial water storage capacity and thus contribute to sea level rise, consequently exacerbating coastal flooding problems. For both methane change and water storage change, wetland dynamics is a crucial factor with the largest uncertainty. Nevertheless, a complete and consistent map of global wetlands still needs to be obtained as the Ramsar Convention calls for a wetlands inventory and impact assessment. We develop a new method for observations of wetland change using Global Navigation Satellite Signals Reflectometry (GNSS-R) signatures for global wetland mapping in synergy with the existing capability, not only as a static inventory but also as a temporal dataset, to advance the capability for monitoring the dynamics of wetland extent relevant to addressing the science issues of CH4 emission change and terrestrial water storage change. We will demonstrate the capability of the new GNSS-R method over a rice field in the Ebro Delta wetland in Spain.

Changes in actin dynamics are involved in salicylic acid signaling pathway.

PubMed

Matoušková, Jindřiška; Janda, Martin; Fišer, Radovan; Sašek, Vladimír; Kocourková, Daniela; Burketová, Lenka; Dušková, Jiřina; Martinec, Jan; Valentová, Olga

2014-06-01

Changes in actin cytoskeleton dynamics are one of the crucial players in many physiological as well as non-physiological processes in plant cells. Positioning of actin filament arrays is necessary for successful establishment of primary lines of defense toward pathogen attack, depolymerization leads very often to the enhanced susceptibility to the invading pathogen. On the other hand it was also shown that the disruption of actin cytoskeleton leads to the induction of defense response leading to the expression of PATHOGENESIS RELATED proteins (PR). In this study we show that pharmacological actin depolymerization leads to the specific induction of genes in salicylic acid pathway but not that involved in jasmonic acid signaling. Life imaging of leafs of Arabidopsis thaliana with GFP-tagged fimbrin (GFP-fABD2) treated with 1 mM salicylic acid revealed rapid disruption of actin filaments resembling the pattern viewed after treatment with 200 nM latrunculin B. The effect of salicylic acid on actin filament fragmentation was prevented by exogenous addition of phosphatidic acid, which binds to the capping protein and thus promotes actin polymerization. The quantitative evaluation of actin filament dynamics is also presented. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Discovery of Intramolecular Signal Transduction Network Based on a New Protein Dynamics Model of Energy Dissipation

PubMed Central

Ma, Cheng-Wei; Xiu, Zhi-Long; Zeng, An-Ping

2012-01-01

A novel approach to reveal intramolecular signal transduction network is proposed in this work. To this end, a new algorithm of network construction is developed, which is based on a new protein dynamics model of energy dissipation. A key feature of this approach is that direction information is specified after inferring protein residue-residue interaction network involved in the process of signal transduction. This enables fundamental analysis of the regulation hierarchy and identification of regulation hubs of the signaling network. A well-studied allosteric enzyme, E. coli aspartokinase III, is used as a model system to demonstrate the new method. Comparison with experimental results shows that the new approach is able to predict all the sites that have been experimentally proved to desensitize allosteric regulation of the enzyme. In addition, the signal transduction network shows a clear preference for specific structural regions, secondary structural types and residue conservation. Occurrence of super-hubs in the network indicates that allosteric regulation tends to gather residues with high connection ability to collectively facilitate the signaling process. Furthermore, a new parameter of propagation coefficient is defined to determine the propagation capability of residues within a signal transduction network. In conclusion, the new approach is useful for fundamental understanding of the process of intramolecular signal transduction and thus has significant impact on rational design of novel allosteric proteins. PMID:22363664

Scaling analyses of the spectral dimension in 3-dimensional causal dynamical triangulations

NASA Astrophysics Data System (ADS)

Cooperman, Joshua H.

2018-05-01

The spectral dimension measures the dimensionality of a space as witnessed by a diffusing random walker. Within the causal dynamical triangulations approach to the quantization of gravity (Ambjørn et al 2000 Phys. Rev. Lett. 85 347, 2001 Nucl. Phys. B 610 347, 1998 Nucl. Phys. B 536 407), the spectral dimension exhibits novel scale-dependent dynamics: reducing towards a value near 2 on sufficiently small scales, matching closely the topological dimension on intermediate scales, and decaying in the presence of positive curvature on sufficiently large scales (Ambjørn et al 2005 Phys. Rev. Lett. 95 171301, Ambjørn et al 2005 Phys. Rev. D 72 064014, Benedetti and Henson 2009 Phys. Rev. D 80 124036, Cooperman 2014 Phys. Rev. D 90 124053, Cooperman et al 2017 Class. Quantum Grav. 34 115008, Coumbe and Jurkiewicz 2015 J. High Energy Phys. JHEP03(2015)151, Kommu 2012 Class. Quantum Grav. 29 105003). I report the first comprehensive scaling analysis of the small-to-intermediate scale spectral dimension for the test case of the causal dynamical triangulations of 3-dimensional Einstein gravity. I find that the spectral dimension scales trivially with the diffusion constant. I find that the spectral dimension is completely finite in the infinite volume limit, and I argue that its maximal value is exactly consistent with the topological dimension of 3 in this limit. I find that the spectral dimension reduces further towards a value near 2 as this case’s bare coupling approaches its phase transition, and I present evidence against the conjecture that the bare coupling simply sets the overall scale of the quantum geometry (Ambjørn et al 2001 Phys. Rev. D 64 044011). On the basis of these findings, I advance a tentative physical explanation for the dynamical reduction of the spectral dimension observed within causal dynamical triangulations: branched polymeric quantum geometry on sufficiently small scales. My analyses should facilitate attempts to employ the spectral

Ras plasma membrane signalling platforms

PubMed Central

2005-01-01

The plasma membrane is a complex, dynamic structure that provides platforms for the assembly of many signal transduction pathways. These platforms have the capacity to impose an additional level of regulation on cell signalling networks. In this review, we will consider specifically how Ras proteins interact with the plasma membrane. The focus will be on recent studies that provide novel spatial and dynamic insights into the micro-environments that different Ras proteins utilize for signal transduction. We will correlate these recent studies suggesting Ras proteins might operate within a heterogeneous plasma membrane with earlier biochemical work on Ras signal transduction. PMID:15954863

Methodology in the assessment of complex human performance : the effects of signal rate on monitoring a dynamic process.

DOT National Transportation Integrated Search

1969-04-01

Male subjects were tested after extensive training as two five-man 'crews' in an experiment designed to examine the effects of signal rate on the performance of a task involving the monitoring of a dynamic process. Performance was measured using thre...

Pulsatile Hormonal Signaling to Extracellular Signal-regulated Kinase

PubMed Central

Perrett, Rebecca M.; Voliotis, Margaritis; Armstrong, Stephen P.; Fowkes, Robert C.; Pope, George R.; Tsaneva-Atanasova, Krasimira; McArdle, Craig A.

2014-01-01

Gonadotropin-releasing hormone (GnRH) is secreted in brief pulses that stimulate synthesis and secretion of pituitary gonadotropin hormones and thereby mediate control of reproduction. It acts via G-protein-coupled receptors to stimulate effectors, including ERK. Information could be encoded in GnRH pulse frequency, width, amplitude, or other features of pulse shape, but the relative importance of these features is unknown. Here we examine this using automated fluorescence microscopy and mathematical modeling, focusing on ERK signaling. The simplest scenario is one in which the system is linear, and response dynamics are relatively fast (compared with the signal dynamics). In this case integrated system output (ERK activation or ERK-driven transcription) will be roughly proportional to integrated input, but we find that this is not the case. Notably, we find that relatively slow response kinetics lead to ERK activity beyond the GnRH pulse, and this reduces sensitivity to pulse width. More generally, we show that the slowing of response kinetics through the signaling cascade creates a system that is robust to pulse width. We, therefore, show how various levels of response kinetics synergize to dictate system sensitivity to different features of pulsatile hormone input. We reveal the mathematical and biochemical basis of a dynamic GnRH signaling system that is robust to changes in pulse amplitude and width but is sensitive to changes in receptor occupancy and frequency, precisely the features that are tightly regulated and exploited to exert physiological control in vivo. PMID:24482225

Who Is Overeducated and Why? Probit and Dynamic Mixed Multinomial Logit Analyses of Vertical Mismatch in East and West Germany

ERIC Educational Resources Information Center

Boll, Christina; Leppin, Julian Sebastian; Schömann, Klaus

2016-01-01

Overeducation potentially signals a productivity loss. With Socio-Economic Panel data from 1984 to 2011 we identify drivers of educational mismatch for East and West medium and highly educated Germans. Addressing measurement error, state dependence and unobserved heterogeneity, we run dynamic mixed multinomial logit models for three different…

Human-arm-and-hand-dynamic model with variability analyses for a stylus-based haptic interface.

PubMed

Fu, Michael J; Cavuşoğlu, M Cenk

2012-12-01

Haptic interface research benefits from accurate human arm models for control and system design. The literature contains many human arm dynamic models but lacks detailed variability analyses. Without accurate measurements, variability is modeled in a very conservative manner, leading to less than optimal controller and system designs. This paper not only presents models for human arm dynamics but also develops inter- and intrasubject variability models for a stylus-based haptic device. Data from 15 human subjects (nine male, six female, ages 20-32) were collected using a Phantom Premium 1.5a haptic device for system identification. In this paper, grip-force-dependent models were identified for 1-3-N grip forces in the three spatial axes. Also, variability due to human subjects and grip-force variation were modeled as both structured and unstructured uncertainties. For both forms of variability, the maximum variation, 95 %, and 67 % confidence interval limits were examined. All models were in the frequency domain with force as input and position as output. The identified models enable precise controllers targeted to a subset of possible human operator dynamics.

DYNAMICS OF EXTRACELLULAR SIGNAL-REGULATED KINASE (ERK) ACTIVATION IN DEVELOPING CEREBELLAR GRANULE CELLS (CGC): A SYSTEMS BIOLOGY-ORIENTED STUDY

EPA Science Inventory

The objective of this study was to 1) characterize the dynamics of ERK activation in response to BDNF and NMDA; 2) use computational models to promote understanding of the signaling network underlying ERK activation.

Scale-Free and Multifractal Time Dynamics of fMRI Signals during Rest and Task

PubMed Central

Ciuciu, P.; Varoquaux, G.; Abry, P.; Sadaghiani, S.; Kleinschmidt, A.

2012-01-01

Scaling temporal dynamics in functional MRI (fMRI) signals have been evidenced for a decade as intrinsic characteristics of ongoing brain activity (Zarahn et al., 1997). Recently, scaling properties were shown to fluctuate across brain networks and to be modulated between rest and task (He, 2011): notably, Hurst exponent, quantifying long memory, decreases under task in activating and deactivating brain regions. In most cases, such results were obtained: First, from univariate (voxelwise or regionwise) analysis, hence focusing on specific cognitive systems such as Resting-State Networks (RSNs) and raising the issue of the specificity of this scale-free dynamics modulation in RSNs. Second, using analysis tools designed to measure a single scaling exponent related to the second order statistics of the data, thus relying on models that either implicitly or explicitly assume Gaussianity and (asymptotic) self-similarity, while fMRI signals may significantly depart from those either of those two assumptions (Ciuciu et al., 2008; Wink et al., 2008). To address these issues, the present contribution elaborates on the analysis of the scaling properties of fMRI temporal dynamics by proposing two significant variations. First, scaling properties are technically investigated using the recently introduced Wavelet Leader-based Multifractal formalism (WLMF; Wendt et al., 2007). This measures a collection of scaling exponents, thus enables a richer and more versatile description of scale invariance (beyond correlation and Gaussianity), referred to as multifractality. Also, it benefits from improved estimation performance compared to tools previously used in the literature. Second, scaling properties are investigated in both RSN and non-RSN structures (e.g., artifacts), at a broader spatial scale than the voxel one, using a multivariate approach, namely the Multi-Subject Dictionary Learning (MSDL) algorithm (Varoquaux et al., 2011) that produces a set of spatial components that

Dissecting the Calcium-Induced Differentiation of Human Primary Keratinocytes Stem Cells by Integrative and Structural Network Analyses

PubMed Central

Toufighi, Kiana; Yang, Jae-Seong; Luis, Nuno Miguel; Aznar Benitah, Salvador; Lehner, Ben; Serrano, Luis; Kiel, Christina

2015-01-01

The molecular details underlying the time-dependent assembly of protein complexes in cellular networks, such as those that occur during differentiation, are largely unexplored. Focusing on the calcium-induced differentiation of primary human keratinocytes as a model system for a major cellular reorganization process, we look at the expression of genes whose products are involved in manually-annotated protein complexes. Clustering analyses revealed only moderate co-expression of functionally related proteins during differentiation. However, when we looked at protein complexes, we found that the majority (55%) are composed of non-dynamic and dynamic gene products (‘di-chromatic’), 19% are non-dynamic, and 26% only dynamic. Considering three-dimensional protein structures to predict steric interactions, we found that proteins encoded by dynamic genes frequently interact with a common non-dynamic protein in a mutually exclusive fashion. This suggests that during differentiation, complex assemblies may also change through variation in the abundance of proteins that compete for binding to common proteins as found in some cases for paralogous proteins. Considering the example of the TNF-α/NFκB signaling complex, we suggest that the same core complex can guide signals into diverse context-specific outputs by addition of time specific expressed subunits, while keeping other cellular functions constant. Thus, our analysis provides evidence that complex assembly with stable core components and competition could contribute to cell differentiation. PMID:25946651

Analyses of the soil surface dynamic of South African Kalahari salt pans based on hyperspectral and multitemporal data

NASA Astrophysics Data System (ADS)

Milewski, Robert; Chabrillat, Sabine; Behling, Robert; Mielke, Christian; Schleicher, Anja Maria; Guanter, Luis

2016-04-01

The consequences of climate change represent a major threat to sustainable development and growth in Southern Africa. Understanding the impact on the geo- and biosphere is therefore of great importance in this particular region. In this context the Kalahari salt pans (also known as playas or sabkhas) and their peripheral saline and alkaline habitats are an ecosystem of major interest. They are very sensitive to environmental conditions, and as thus hydrological, mineralogical and ecological responses to climatic variations can be analysed. Up to now the soil composition of salt pans in this area have been only assessed mono-temporally and on a coarse regional scale. Furthermore, the dynamic of the salt pans, especially the formation of evaporites, is still uncertain and poorly understood. High spectral resolution remote sensing can estimate evaporite content and mineralogy of soils based on the analyses of the surface reflectance properties within the Visible-Near InfraRed (VNIR 400-1000 nm) and Short-Wave InfraRed (SWIR 1000-2500 nm) regions. In these wavelength regions major chemical components of the soil interact with the electromagnetic radiation and produce characteristic absorption features that can be used to derive the properties of interest. Although such techniques are well established for the laboratory and field scale, the potential of current (Hyperion) and upcoming spaceborne sensors such as EnMAP for quantitative mineralogical and salt spectral mapping is still to be demonstrated. Combined with hyperspectral methods, multitemporal remote sensing techniques allow us to derive the recent dynamic of these salt pans and link the mineralogical analysis of the pan surface to major physical processes in these dryland environments. In this study we focus on the analyses of the Namibian Omongwa salt pans based on satellite hyperspectral imagery and multispectral time-series data. First, a change detection analysis is applied using the Iterative

Resolving dynamics of cell signaling via real-time imaging of the immunological synapse.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stevens, Mark A.; Pfeiffer, Janet R.; Wilson, Bridget S.

2009-10-01

This highly interdisciplinary team has developed dual-color, total internal reflection microscopy (TIRF-M) methods that enable us to optically detect and track in real time protein migration and clustering at membrane interfaces. By coupling TIRF-M with advanced analysis techniques (image correlation spectroscopy, single particle tracking) we have captured subtle changes in membrane organization that characterize immune responses. We have used this approach to elucidate the initial stages of cell activation in the IgE signaling network of mast cells and the Toll-like receptor (TLR-4) response in macrophages stimulated by bacteria. To help interpret these measurements, we have undertaken a computational modeling effortmore » to connect the protein motion and lipid interactions. This work provides a deeper understanding of the initial stages of cellular response to external agents, including dynamics of interaction of key components in the signaling network at the 'immunological synapse,' the contact region of the cell and its adversary.« less

Signal Processing Methods for Liquid Rocket Engine Combustion Stability Assessments

NASA Technical Reports Server (NTRS)

Kenny, R. Jeremy; Lee, Erik; Hulka, James R.; Casiano, Matthew

2011-01-01

The J2X Gas Generator engine design specifications include dynamic, spontaneous, and broadband combustion stability requirements. These requirements are verified empirically based high frequency chamber pressure measurements and analyses. Dynamic stability is determined with the dynamic pressure response due to an artificial perturbation of the combustion chamber pressure (bomb testing), and spontaneous and broadband stability are determined from the dynamic pressure responses during steady operation starting at specified power levels. J2X Workhorse Gas Generator testing included bomb tests with multiple hardware configurations and operating conditions, including a configuration used explicitly for engine verification test series. This work covers signal processing techniques developed at Marshall Space Flight Center (MSFC) to help assess engine design stability requirements. Dynamic stability assessments were performed following both the CPIA 655 guidelines and a MSFC in-house developed statistical-based approach. The statistical approach was developed to better verify when the dynamic pressure amplitudes corresponding to a particular frequency returned back to pre-bomb characteristics. This was accomplished by first determining the statistical characteristics of the pre-bomb dynamic levels. The pre-bomb statistical characterization provided 95% coverage bounds; these bounds were used as a quantitative measure to determine when the post-bomb signal returned to pre-bomb conditions. The time for post-bomb levels to acceptably return to pre-bomb levels was compared to the dominant frequency-dependent time recommended by CPIA 655. Results for multiple test configurations, including stable and unstable configurations, were reviewed. Spontaneous stability was assessed using two processes: 1) characterization of the ratio of the peak response amplitudes to the excited chamber acoustic mode amplitudes and 2) characterization of the variability of the peak response

Dynamic control of type I IFN signalling by an integrated network of negative regulators.

PubMed

Porritt, Rebecca A; Hertzog, Paul J

2015-03-01

Whereas type I interferons (IFNs) have critical roles in protection from pathogens, excessive IFN responses contribute to pathology in both acute and chronic settings, pointing to the importance of balancing activating signals with regulatory mechanisms that appropriately tune the response. Here we review evidence for an integrated network of negative regulators of IFN production and action, which function at all levels of the activating and effector signalling pathways. We propose that the aim of this extensive network is to limit tissue damage while enabling an IFN response that is temporally appropriate and of sufficient magnitude. Understanding the architecture and dynamics of this network, and how it differs in distinct tissues, will provide new insights into IFN biology and aid the design of more effective therapeutics. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Bmp signaling mediates endoderm pouch morphogenesis by regulating Fgf signaling in zebrafish

PubMed Central

Swartz, Mary E.; McCarthy, Neil; Norrie, Jacqueline L.; Eberhart, Johann K.

2016-01-01

The endodermal pouches are a series of reiterated structures that segment the pharyngeal arches and help pattern the vertebrate face. Multiple pathways regulate the complex process of endodermal development, including the Bone morphogenetic protein (Bmp) pathway. However, the role of Bmp signaling in pouch morphogenesis is poorly understood. Using genetic and chemical inhibitor approaches, we show that pouch morphogenesis requires Bmp signaling from 10-18 h post-fertilization, immediately following gastrulation. Blocking Bmp signaling during this window results in morphological defects to the pouches and craniofacial skeleton. Using genetic chimeras we show that Bmp signals directly to the endoderm for proper morphogenesis. Time-lapse imaging and analysis of reporter transgenics show that Bmp signaling is necessary for pouch outpocketing via the Fibroblast growth factor (Fgf) pathway. Double loss-of-function analyses demonstrate that Bmp and Fgf signaling interact synergistically in craniofacial development. Collectively, our analyses shed light on the tissue and signaling interactions that regulate development of the vertebrate face. PMID:27122171

The spatiotemporal order of signaling events unveils the logic of development signaling.

PubMed

Zhu, Hao; Owen, Markus R; Mao, Yanlan

2016-08-01

Animals from worms and insects to birds and mammals show distinct body plans; however, the embryonic development of diverse body plans with tissues and organs within is controlled by a surprisingly few signaling pathways. It is well recognized that combinatorial use of and dynamic interactions among signaling pathways follow specific logic to control complex and accurate developmental signaling and patterning, but it remains elusive what such logic is, or even, what it looks like. We have developed a computational model for Drosophila eye development with innovated methods to reveal how interactions among multiple pathways control the dynamically generated hexagonal array of R8 cells. We obtained two novel findings. First, the coupling between the long-range inductive signals produced by the proneural Hh signaling and the short-range restrictive signals produced by the antineural Notch and EGFR signaling is essential for generating accurately spaced R8s. Second, the spatiotemporal orders of key signaling events reveal a robust pattern of lateral inhibition conducted by Ato-coordinated Notch and EGFR signaling to collectively determine R8 patterning. This pattern, stipulating the orders of signaling and comparable to the protocols of communication, may help decipher the well-appreciated but poorly defined logic of developmental signaling. The model is available upon request. hao.zhu@ymail.com Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

The spatiotemporal order of signaling events unveils the logic of development signaling

PubMed Central

Zhu, Hao; Owen, Markus R.; Mao, Yanlan

2016-01-01

Motivation: Animals from worms and insects to birds and mammals show distinct body plans; however, the embryonic development of diverse body plans with tissues and organs within is controlled by a surprisingly few signaling pathways. It is well recognized that combinatorial use of and dynamic interactions among signaling pathways follow specific logic to control complex and accurate developmental signaling and patterning, but it remains elusive what such logic is, or even, what it looks like. Results: We have developed a computational model for Drosophila eye development with innovated methods to reveal how interactions among multiple pathways control the dynamically generated hexagonal array of R8 cells. We obtained two novel findings. First, the coupling between the long-range inductive signals produced by the proneural Hh signaling and the short-range restrictive signals produced by the antineural Notch and EGFR signaling is essential for generating accurately spaced R8s. Second, the spatiotemporal orders of key signaling events reveal a robust pattern of lateral inhibition conducted by Ato-coordinated Notch and EGFR signaling to collectively determine R8 patterning. This pattern, stipulating the orders of signaling and comparable to the protocols of communication, may help decipher the well-appreciated but poorly defined logic of developmental signaling. Availability and implementation: The model is available upon request. Contact: hao.zhu@ymail.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153573

Analysing Structure Dynamics in Arable Soils using X-ray Micro-Tomography

NASA Astrophysics Data System (ADS)

Schlüter, S.; Weller, U.; Vogel, H.-J.

2009-04-01

Structure is a dynamic property of soil. It interacts with many biotic and abiotic features and controls various soil functions. We analyzed soil structure within different plots of the ''Static Fertilisation Experiment'' at the agricultural research station in Bad Lauchstaedt (Germany) using X-ray micro tomography. The aim was to investigate in how far different levels of organic carbon, increased microbial activity and enhanced plant growth affects structural properties of an arable soil. Since 106 years one plot has experienced a constant application of farmyard manure and fertilisers, whereas the other has never been fertilised in this period. Intact soil cores from the chernozem soil at the two plots were taken from a depth of 5 to 15 cm (Ap-horizon) and 35 to 45 cm (Ah-horizon) to analyse structural changes with depth and in two different seasons (spring and summer) to investigate structure dynamics. The pore structure was analysed by quantifying the mean geometrical and topological characteristics of the pore network as a function of pore size. This was done by a combination of Minkowski functionals and morphological size distibution. For small structural features close to the image resolution the results clearly depend on the applied filtering technique and segmentation thresholds. Therefore the application of different image enhancement techniques is discussed. Furthermore, a new method for an automated determination of grey value thesholds for the segmentation of CT-images into pore space and solid is developed and evaluated. We highlight the relevance of image resolution for structure analysis. Results of the structure analysis reveal that the spring samples of the ploughed layer (Ap-horizon) from the fertilised plot have significantly higher macroporosities (P < 0.05) than those from the non-fertilised plot. The internal connectivity of the pore network is better in the fertilised plot and the pore size distribution was found to be different, too. The

Structural connectome topology relates to regional BOLD signal dynamics in the mouse brain

NASA Astrophysics Data System (ADS)

Sethi, Sarab S.; Zerbi, Valerio; Wenderoth, Nicole; Fornito, Alex; Fulcher, Ben D.

2017-04-01

Brain dynamics are thought to unfold on a network determined by the pattern of axonal connections linking pairs of neuronal elements; the so-called connectome. Prior work has indicated that structural brain connectivity constrains pairwise correlations of brain dynamics ("functional connectivity"), but it is not known whether inter-regional axonal connectivity is related to the intrinsic dynamics of individual brain areas. Here we investigate this relationship using a weighted, directed mesoscale mouse connectome from the Allen Mouse Brain Connectivity Atlas and resting state functional MRI (rs-fMRI) time-series data measured in 184 brain regions in eighteen anesthetized mice. For each brain region, we measured degree, betweenness, and clustering coefficient from weighted and unweighted, and directed and undirected versions of the connectome. We then characterized the univariate rs-fMRI dynamics in each brain region by computing 6930 time-series properties using the time-series analysis toolbox, hctsa. After correcting for regional volume variations, strong and robust correlations between structural connectivity properties and rs-fMRI dynamics were found only when edge weights were accounted for, and were associated with variations in the autocorrelation properties of the rs-fMRI signal. The strongest relationships were found for weighted in-degree, which was positively correlated to the autocorrelation of fMRI time series at time lag τ = 34 s (partial Spearman correlation ρ = 0.58 ), as well as a range of related measures such as relative high frequency power (f > 0.4 Hz: ρ = - 0.43 ). Our results indicate that the topology of inter-regional axonal connections of the mouse brain is closely related to intrinsic, spontaneous dynamics such that regions with a greater aggregate strength of incoming projections display longer timescales of activity fluctuations.

Visualization of Notch signaling oscillation in cells and tissues.

PubMed

Shimojo, Hiromi; Harima, Yukiko; Kageyama, Ryoichiro

2014-01-01

The Notch signaling effectors Hes1 and Hes7 exhibit oscillatory expression with a period of about 2-3 h during embryogenesis. Hes1 oscillation is important for proliferation and differentiation of neural stem cells, whereas Hes7 oscillation regulates periodic formation of somites. Continuous expression of Hes1 and Hes7 inhibits these developmental processes. Thus, expression dynamics are very important for gene functions, but it is difficult to distinguish between oscillatory and persistent expression by conventional methods such as in situ hybridization and immunostaining. Here, we describe time-lapse imaging methods using destabilized luciferase reporters and a highly sensitive cooled charge-coupled device camera, which can monitor dynamic gene expression. Furthermore, the expression of two genes can be examined simultaneously by a dual reporter system using two-color luciferase reporters. Time-lapse imaging analyses reveal how dynamically gene expression changes in many biological events.

Ubx dynamically regulates Dpp signaling by repressing Dad expression during copper cell regeneration in the adult Drosophila midgut

PubMed Central

Li, Hongjie; Qi, Yanyan; Jasper, Heinrich

2016-01-01

The gastrointestinal (GI) tract of metazoans is lined by a series of regionally distinct epithelia. To maintain structure and function of the GI tract, regionally diversified differentiation of somatic stem cell (SC) lineages is critical. The adult Drosophila midgut provides an accessible model to study SC regulation and specification in a regionally defined manner. SCs of the posterior midgut (PM) have been studied extensively, but the control of SCs in the middle midgut (MM) is less well understood. The MM contains a stomach-like copper cell region (CCR) that is regenerated by gastric stem cells (GSSCs) and contains acid-secreting copper cells (CCs). Bmp-like Decapentaplegic (Dpp) signaling determines the identity of GSSCs, and is required for CC regeneration, yet the precise control of Dpp signaling activity in this lineage remains to be fully established. Here, we show that Dad, a negative feedback regulator of Dpp signaling, is dynamically regulated in the GSSC lineage to allow CC differentiation. Dad is highly expressed in GSSCs and their first daughter cells, the gastroblasts (GBs), but has to be repressed in differentiating CCs to allow Dpp-mediated differentiation into CCs. We find that the Hox gene ultrabithorax (Ubx) is required for this regulation. Loss of Ubx prevents Dad repression in the CCR, resulting in defective CC regeneration. Our study highlights the need for dynamic control of Dpp signaling activity in the differentiation of the GSSC lineage and identifies Ubx as a critical regulator of this process. PMID:27570230

Performance Metrics for Liquid Chromatography-Tandem Mass Spectrometry Systems in Proteomics Analyses*

PubMed Central

Rudnick, Paul A.; Clauser, Karl R.; Kilpatrick, Lisa E.; Tchekhovskoi, Dmitrii V.; Neta, Pedatsur; Blonder, Nikša; Billheimer, Dean D.; Blackman, Ronald K.; Bunk, David M.; Cardasis, Helene L.; Ham, Amy-Joan L.; Jaffe, Jacob D.; Kinsinger, Christopher R.; Mesri, Mehdi; Neubert, Thomas A.; Schilling, Birgit; Tabb, David L.; Tegeler, Tony J.; Vega-Montoto, Lorenzo; Variyath, Asokan Mulayath; Wang, Mu; Wang, Pei; Whiteaker, Jeffrey R.; Zimmerman, Lisa J.; Carr, Steven A.; Fisher, Susan J.; Gibson, Bradford W.; Paulovich, Amanda G.; Regnier, Fred E.; Rodriguez, Henry; Spiegelman, Cliff; Tempst, Paul; Liebler, Daniel C.; Stein, Stephen E.

2010-01-01

A major unmet need in LC-MS/MS-based proteomics analyses is a set of tools for quantitative assessment of system performance and evaluation of technical variability. Here we describe 46 system performance metrics for monitoring chromatographic performance, electrospray source stability, MS1 and MS2 signals, dynamic sampling of ions for MS/MS, and peptide identification. Applied to data sets from replicate LC-MS/MS analyses, these metrics displayed consistent, reasonable responses to controlled perturbations. The metrics typically displayed variations less than 10% and thus can reveal even subtle differences in performance of system components. Analyses of data from interlaboratory studies conducted under a common standard operating procedure identified outlier data and provided clues to specific causes. Moreover, interlaboratory variation reflected by the metrics indicates which system components vary the most between laboratories. Application of these metrics enables rational, quantitative quality assessment for proteomics and other LC-MS/MS analytical applications. PMID:19837981

Low-rank and Adaptive Sparse Signal (LASSI) Models for Highly Accelerated Dynamic Imaging

PubMed Central

Ravishankar, Saiprasad; Moore, Brian E.; Nadakuditi, Raj Rao; Fessler, Jeffrey A.

2017-01-01

Sparsity-based approaches have been popular in many applications in image processing and imaging. Compressed sensing exploits the sparsity of images in a transform domain or dictionary to improve image recovery from undersampled measurements. In the context of inverse problems in dynamic imaging, recent research has demonstrated the promise of sparsity and low-rank techniques. For example, the patches of the underlying data are modeled as sparse in an adaptive dictionary domain, and the resulting image and dictionary estimation from undersampled measurements is called dictionary-blind compressed sensing, or the dynamic image sequence is modeled as a sum of low-rank and sparse (in some transform domain) components (L+S model) that are estimated from limited measurements. In this work, we investigate a data-adaptive extension of the L+S model, dubbed LASSI, where the temporal image sequence is decomposed into a low-rank component and a component whose spatiotemporal (3D) patches are sparse in some adaptive dictionary domain. We investigate various formulations and efficient methods for jointly estimating the underlying dynamic signal components and the spatiotemporal dictionary from limited measurements. We also obtain efficient sparsity penalized dictionary-blind compressed sensing methods as special cases of our LASSI approaches. Our numerical experiments demonstrate the promising performance of LASSI schemes for dynamic magnetic resonance image reconstruction from limited k-t space data compared to recent methods such as k-t SLR and L+S, and compared to the proposed dictionary-blind compressed sensing method. PMID:28092528

Design and fabrication of a multi-layered solid dynamic phantom: validation platform on methods for reducing scalp-hemodynamic effect from fNIRS signal

NASA Astrophysics Data System (ADS)

Kawaguchi, Hiroshi; Tanikawa, Yukari; Yamada, Toru

2017-02-01

Scalp hemodynamics contaminates the signals from functional near-infrared spectroscopy (fNIRS). Numerous methods have been proposed to reduce this contamination, but no golden standard has yet been established. Here we constructed a multi-layered solid phantom to experimentally validate such methods. This phantom comprises four layers corresponding to epidermides, dermis/skull (upper dynamic layer), cerebrospinal fluid and brain (lower dynamic layer) and the thicknesses of these layers were 0.3, 10, 1, and 50 mm, respectively. The epidermides and cerebrospinal fluid layers were made of polystyrene and an acrylic board, respectively. Both of these dynamic layers were made of epoxy resin. An infrared dye and titanium dioxide were mixed to match their absorption and reduced scattering coefficients (μa and μs', respectively) with those of biological tissues. The bases of both upper and lower dynamic layers have a slot for laterally sliding a bar that holds an absorber piece. This bar was laterally moved using a programmable stepping motor. The optical properties of dynamic layers were estimated based on the transmittance and reflectance using the Monte Carlo look-up table method. The estimated coefficients for lower and upper dynamic layers approximately coincided with those for biological tissues. We confirmed that the preliminary fNIRS measurement using the fabricated phantom showed that the signals from the brain layer were recovered if those from the dermis layer were completely removed from their mixture, indicating that the phantom is useful for evaluating methods for reducing the contamination of the signals from the scalp.

Structural and Dynamic Insights into the Mechanism of Allosteric Signal Transmission in ERK2-Mediated MKP3 Activation.

PubMed

Lu, Chang; Liu, Xin; Zhang, Chen-Song; Gong, Haipeng; Wu, Jia-Wei; Wang, Zhi-Xin

2017-11-21

The mitogen-activated protein kinases (MAPKs) are key components of cellular signal transduction pathways, which are down-regulated by the MAPK phosphatases (MKPs). Catalytic activity of the MKPs is controlled both by their ability to recognize selective MAPKs and by allosteric activation upon binding to MAPK substrates. Here, we use a combination of experimental and computational techniques to elucidate the molecular mechanism for the ERK2-induced MKP3 activation. Mutational and kinetic study shows that the 334 FNFM 337 motif in the MKP3 catalytic domain is essential for MKP3-mediated ERK2 inactivation and is responsible for ERK2-mediated MKP3 activation. The long-term molecular dynamics (MD) simulations further reveal a complete dynamic process in which the catalytic domain of MKP3 gradually changes to a conformation that resembles an active MKP catalytic domain over the time scale of the simulation, providing a direct time-dependent observation of allosteric signal transmission in ERK2-induced MKP3 activation.

Using dynamic population simulations to extend resource selection analyses and prioritize habitats for conservation

USGS Publications Warehouse

Heinrichs, Julie; Aldridge, Cameron L.; O'Donnell, Michael; Schumaker, Nathan

2017-01-01

Prioritizing habitats for conservation is a challenging task, particularly for species with fluctuating populations and seasonally dynamic habitat needs. Although the use of resource selection models to identify and prioritize habitat for conservation is increasingly common, their ability to characterize important long-term habitats for dynamic populations are variable. To examine how habitats might be prioritized differently if resource selection was directly and dynamically linked with population fluctuations and movement limitations among seasonal habitats, we constructed a spatially explicit individual-based model for a dramatically fluctuating population requiring temporally varying resources. Using greater sage-grouse (Centrocercus urophasianus) in Wyoming as a case study, we used resource selection function maps to guide seasonal movement and habitat selection, but emergent population dynamics and simulated movement limitations modified long-term habitat occupancy. We compared priority habitats in RSF maps to long-term simulated habitat use. We examined the circumstances under which the explicit consideration of movement limitations, in combination with population fluctuations and trends, are likely to alter predictions of important habitats. In doing so, we assessed the future occupancy of protected areas under alternative population and habitat conditions. Habitat prioritizations based on resource selection models alone predicted high use in isolated parcels of habitat and in areas with low connectivity among seasonal habitats. In contrast, results based on more biologically-informed simulations emphasized central and connected areas near high-density populations, sometimes predicted to be low selection value. Dynamic models of habitat use can provide additional biological realism that can extend, and in some cases, contradict habitat use predictions generated from short-term or static resource selection analyses. The explicit inclusion of population

Bmp signaling mediates endoderm pouch morphogenesis by regulating Fgf signaling in zebrafish.

PubMed

Lovely, C Ben; Swartz, Mary E; McCarthy, Neil; Norrie, Jacqueline L; Eberhart, Johann K

2016-06-01

The endodermal pouches are a series of reiterated structures that segment the pharyngeal arches and help pattern the vertebrate face. Multiple pathways regulate the complex process of endodermal development, including the Bone morphogenetic protein (Bmp) pathway. However, the role of Bmp signaling in pouch morphogenesis is poorly understood. Using genetic and chemical inhibitor approaches, we show that pouch morphogenesis requires Bmp signaling from 10-18 h post-fertilization, immediately following gastrulation. Blocking Bmp signaling during this window results in morphological defects to the pouches and craniofacial skeleton. Using genetic chimeras we show that Bmp signals directly to the endoderm for proper morphogenesis. Time-lapse imaging and analysis of reporter transgenics show that Bmp signaling is necessary for pouch outpocketing via the Fibroblast growth factor (Fgf) pathway. Double loss-of-function analyses demonstrate that Bmp and Fgf signaling interact synergistically in craniofacial development. Collectively, our analyses shed light on the tissue and signaling interactions that regulate development of the vertebrate face. © 2016. Published by The Company of Biologists Ltd.

Coupled stochastic spatial and non-spatial simulations of ErbB1 signaling pathways demonstrate the importance of spatial organization in signal transduction.

PubMed

Costa, Michelle N; Radhakrishnan, Krishnan; Wilson, Bridget S; Vlachos, Dionisios G; Edwards, Jeremy S

2009-07-23

The ErbB family of receptors activates intracellular signaling pathways that control cellular proliferation, growth, differentiation and apoptosis. Given these central roles, it is not surprising that overexpression of the ErbB receptors is often associated with carcinogenesis. Therefore, extensive laboratory studies have been devoted to understanding the signaling events associated with ErbB activation. Systems biology has contributed significantly to our current understanding of ErbB signaling networks. However, although computational models have grown in complexity over the years, little work has been done to consider the spatial-temporal dynamics of receptor interactions and to evaluate how spatial organization of membrane receptors influences signaling transduction. Herein, we explore the impact of spatial organization of the epidermal growth factor receptor (ErbB1/EGFR) on the initiation of downstream signaling. We describe the development of an algorithm that couples a spatial stochastic model of membrane receptors with a nonspatial stochastic model of the reactions and interactions in the cytosol. This novel algorithm provides a computationally efficient method to evaluate the effects of spatial heterogeneity on the coupling of receptors to cytosolic signaling partners. Mathematical models of signal transduction rarely consider the contributions of spatial organization due to high computational costs. A hybrid stochastic approach simplifies analyses of the spatio-temporal aspects of cell signaling and, as an example, demonstrates that receptor clustering contributes significantly to the efficiency of signal propagation from ligand-engaged growth factor receptors.

Exploring Molecular Mechanisms of Paradoxical Activation in the BRAF Kinase Dimers: Atomistic Simulations of Conformational Dynamics and Modeling of Allosteric Communication Networks and Signaling Pathways

PubMed Central

Tse, Amanda; Verkhivker, Gennady M.

2016-01-01

The recent studies have revealed that most BRAF inhibitors can paradoxically induce kinase activation by promoting dimerization and enzyme transactivation. Despite rapidly growing number of structural and functional studies about the BRAF dimer complexes, the molecular basis of paradoxical activation phenomenon is poorly understood and remains largely hypothetical. In this work, we have explored the relationships between inhibitor binding, protein dynamics and allosteric signaling in the BRAF dimers using a network-centric approach. Using this theoretical framework, we have combined molecular dynamics simulations with coevolutionary analysis and modeling of the residue interaction networks to determine molecular determinants of paradoxical activation. We have investigated functional effects produced by paradox inducer inhibitors PLX4720, Dabrafenib, Vemurafenib and a paradox breaker inhibitor PLX7904. Functional dynamics and binding free energy analyses of the BRAF dimer complexes have suggested that negative cooperativity effect and dimer-promoting potential of the inhibitors could be important drivers of paradoxical activation. We have introduced a protein structure network model in which coevolutionary residue dependencies and dynamic maps of residue correlations are integrated in the construction and analysis of the residue interaction networks. The results have shown that coevolutionary residues in the BRAF structures could assemble into independent structural modules and form a global interaction network that may promote dimerization. We have also found that BRAF inhibitors could modulate centrality and communication propensities of global mediating centers in the residue interaction networks. By simulating allosteric communication pathways in the BRAF structures, we have determined that paradox inducer and breaker inhibitors may activate specific signaling routes that correlate with the extent of paradoxical activation. While paradox inducer inhibitors may

A signal-based fault detection and classification method for heavy haul wagons

NASA Astrophysics Data System (ADS)

Li, Chunsheng; Luo, Shihui; Cole, Colin; Spiryagin, Maksym; Sun, Yanquan

2017-12-01

This paper proposes a signal-based fault detection and isolation (FDI) system for heavy haul wagons considering the special requirements of low cost and robustness. The sensor network of the proposed system consists of just two accelerometers mounted on the front left and rear right of the carbody. Seven fault indicators (FIs) are proposed based on the cross-correlation analyses of the sensor-collected acceleration signals. Bolster spring fault conditions are focused on in this paper, including two different levels (small faults and moderate faults) and two locations (faults in the left and right bolster springs of the first bogie). A fully detailed dynamic model of a typical 40t axle load heavy haul wagon is developed to evaluate the deterioration of dynamic behaviour under proposed fault conditions and demonstrate the detectability of the proposed FDI method. Even though the fault conditions considered in this paper did not deteriorate the wagon dynamic behaviour dramatically, the proposed FIs show great sensitivity to the bolster spring faults. The most effective and efficient FIs are chosen for fault detection and classification. Analysis results indicate that it is possible to detect changes in bolster stiffness of ±25% and identify the fault location.

Measurements and analyses of principal dynamic parameters of building structures as a function of type of vibration excitation

NASA Astrophysics Data System (ADS)

Bartmański, Cezary; Bochenek, Wojciech; Passia, Henryk; Szade, Adam

2006-06-01

The methods of direct measurement and analysis of the dynamic response of a building structure through real-time recording of the amplitude of low-frequency vibration (tilt) have been presented. Subject to analyses was the reaction induced either by kinematic excitation (road traffic and mining-induced vibration) or controlled action of solid-fuel rocket micro-engines installed on the building. The forces were analysed by means of a set of transducers installed both in the ground and on the structure. After the action of excitation forces has been stopped, the system (structure) makes damped vibration around the static equilibrium position. It has been shown that the type of excitation affects the accuracy of evaluation of principal dynamic parameters of the structure. In the authors opinion these are the decrement of damping and natural vibration frequency. Positive results of tests with the use of excitation by means of short-action (0.6 second) rocket micro-engines give a chance to develop a reliable method for periodical assessment of acceptable loss of usability characteristics of building structures heavily influenced by environmental effects.

Information flow and protein dynamics: the interplay between nuclear magnetic resonance spectroscopy and molecular dynamics simulations

PubMed Central

Pastor, Nina; Amero, Carlos

2015-01-01

Proteins participate in information pathways in cells, both as links in the chain of signals, and as the ultimate effectors. Upon ligand binding, proteins undergo conformation and motion changes, which can be sensed by the following link in the chain of information. Nuclear magnetic resonance (NMR) spectroscopy and molecular dynamics (MD) simulations represent powerful tools for examining the time-dependent function of biological molecules. The recent advances in NMR and the availability of faster computers have opened the door to more detailed analyses of structure, dynamics, and interactions. Here we briefly describe the recent applications that allow NMR spectroscopy and MD simulations to offer unique insight into the basic motions that underlie information transfer within and between cells. PMID:25999971

Effects of multiple enzyme-substrate interactions in basic units of cellular signal processing

NASA Astrophysics Data System (ADS)

Seaton, D. D.; Krishnan, J.

2012-08-01

Covalent modification cycles are a ubiquitous feature of cellular signalling networks. In these systems, the interaction of an active enzyme with the unmodified form of its substrate is essential for signalling to occur. However, this interaction is not necessarily the only enzyme-substrate interaction possible. In this paper, we analyse the behaviour of a basic model of signalling in which additional, non-essential enzyme-substrate interactions are possible. These interactions include those between the inactive form of an enzyme and its substrate, and between the active form of an enzyme and its product. We find that these additional interactions can result in increased sensitivity and biphasic responses, respectively. The dynamics of the responses are also significantly altered by the presence of additional interactions. Finally, we evaluate the consequences of these interactions in two variations of our basic model, involving double modification of substrate and scaffold-mediated signalling, respectively. We conclude that the molecular details of protein-protein interactions are important in determining the signalling properties of enzymatic signalling pathways.

Structure-Activity Relationship in TLR4 Mutations: Atomistic Molecular Dynamics Simulations and Residue Interaction Network Analysis

NASA Astrophysics Data System (ADS)

Anwar, Muhammad Ayaz; Choi, Sangdun

2017-03-01

Toll-like receptor 4 (TLR4), a vital innate immune receptor present on cell surfaces, initiates a signaling cascade during danger and bacterial intrusion. TLR4 needs to form a stable hexamer complex, which is necessary to dimerize the cytoplasmic domain. However, D299G and T399I polymorphism may abrogate the stability of the complex, leading to compromised TLR4 signaling. Crystallography provides valuable insights into the structural aspects of the TLR4 ectodomain; however, the dynamic behavior of polymorphic TLR4 is still unclear. Here, we employed molecular dynamics simulations (MDS), as well as principal component and residue network analyses, to decipher the structural aspects and signaling propagation associated with mutations in TLR4. The mutated complexes were less cohesive, displayed local and global variation in the secondary structure, and anomalous decay in rotational correlation function. Principal component analysis indicated that the mutated complexes also exhibited distinct low-frequency motions, which may be correlated to the differential behaviors of these TLR4 variants. Moreover, residue interaction networks (RIN) revealed that the mutated TLR4/myeloid differentiation factor (MD) 2 complex may perpetuate abnormal signaling pathways. Cumulatively, the MDS and RIN analyses elucidated the mutant-specific conformational alterations, which may help in deciphering the mechanism of loss-of-function mutations.

Interaction between telencephalic signals and respiratory dynamics in songbirds

PubMed Central

Méndez, Jorge M.; Mindlin, Gabriel B.

2012-01-01

The mechanisms by which telencephalic areas affect motor activities are largely unknown. They could either take over motor control from downstream motor circuits or interact with the intrinsic dynamics of these circuits. Both models have been proposed for telencephalic control of respiration during learned vocal behavior in birds. The interactive model postulates that simple signals from the telencephalic song control areas are sufficient to drive the nonlinear respiratory network into producing complex temporal sequences. We tested this basic assumption by electrically stimulating telencephalic song control areas and analyzing the resulting respiratory patterns in zebra finches and in canaries. We found strong evidence for interaction between the rhythm of stimulation and the intrinsic respiratory rhythm, including naturally emerging subharmonic behavior and integration of lateralized telencephalic input. The evidence for clear interaction in our experimental paradigm suggests that telencephalic vocal control also uses a similar mechanism. Furthermore, species differences in the response of the respiratory system to stimulation show parallels to differences in the respiratory patterns of song, suggesting that the interactive production of respiratory rhythms is manifested in species-specific specialization of the involved circuitry. PMID:22402649

Dynamic behavioral strategies during sonar signal emission in roundleaf bats.

PubMed

Feng, Lin; Li, Yitan; Lu, Hongwang

2013-10-02

For echolocating bats which emit biosonar pulses nasally, their nostrils are surrounded by fleshy appendages that diffract the outgoing ultrasonic waves. The posterior leaf, as a prominent part of the noseleaf, was mentioned in previous preliminary observations to move during flight in some species of bats, yet the detailed motion patterns and thus the possible functional role of the posterior leaf movement in biosonar systems remain unclear. In the current work, the motion of the posterior leaf of living pratt's roundleaf bats has been investigated quantitatively. Temporal characterizations of the noseleaf movement and the ultrasonic pulse emission were performed by virtue of synchronized laser vibrometry and sound recording. The results showed that the posterior leaf tilted forwards and restored to original position within tens of milliseconds. Noseleaf motions were temporally correlated with the emitted ultrasonic pulses. The surfaces of the posterior leaf were moving in the anterior direction in most of the pulse duration. The bats were able to switch the motions on or off. From the comparison with the previously reported noseleaf dynamics in horseshoe bat, we find similar ratio sizes and displacements of the noseleaves compared to the used wavelengths, implying that similar behavioral strategies are utilized by species of bats and it may be applied to different components of the signal emitting apparatus. It suggests that the dynamic sensing principles may widely play a role in the biosonar systems and the investigation on time-variant mechanisms is of capital importance to understand the biosonar sensing strategies used by echolocating bats. © 2013.

Ongoing Analyses of Rocket Based Combined Cycle Engines by the Applied Fluid Dynamics Analysis Group at Marshall Space Flight Center

NASA Technical Reports Server (NTRS)

Ruf, Joseph H.; Holt, James B.; Canabal, Francisco

2001-01-01

This paper presents the status of analyses on three Rocket Based Combined Cycle (RBCC) configurations underway in the Applied Fluid Dynamics Analysis Group (TD64). TD64 is performing computational fluid dynamics (CFD) analysis on a Penn State RBCC test rig, the proposed Draco axisymmetric RBCC engine and the Trailblazer engine. The intent of the analysis on the Penn State test rig is to benchmark the Finite Difference Navier Stokes (FDNS) code for ejector mode fluid dynamics. The Draco analysis was a trade study to determine the ejector mode performance as a function of three engine design variables. The Trailblazer analysis is to evaluate the nozzle performance in scramjet mode. Results to date of each analysis are presented.

The dynamics of sediment size and transient erosional signals in heterogeneous lithologies

NASA Astrophysics Data System (ADS)

Lyons, N. J.; Gasparini, N. M.; Crosby, B. T.; Wehrs, K.; Willenbring, J. K.

2017-12-01

Sediment supply and transport dynamics convey, transform, and destroy climatic and tectonic signals in channels and depositional landforms. The South Fork Eel River (SFER) in the northern California Coast Ranges, USA exhibits characteristics suggestive of transient landscape adjustment: strath terraces, knickpoints, and headwater terrain eroding more slowly than downstream areas. A tectonically-induced uplift wave is commonly invoked as the driver of transience in this region. The wave is attributed to the northward migration of the Mendocino Triple Junction (MTJ). Nested basin-mean erosion rates calculated from 10Be detrital quartz sand increase down the mainstem of the SFER, roughly coinciding with the direction of MTJ migration. This erosion trend is attributed to the proportion of adjusted and unadjusted landscape portions upstream of the locations where the nested 10Be samples were collected. Adjusted and unadjusted landscape portions are separated by a broad knickzone that contains 28% of relief along the mainstem. Knickzone propagation and considerable stream incision is suggested by projection of the upper SFER above the knickzone through the highest flight of strath terraces. Field observations and outcomes of numerical simulations using the Landlab modeling framework are incompatible with uplift modeled as a wave. Alternative uplift and variable sediment flux scenarios more reliably predict the pattern of terraces, knickpoints, and accelerated erosion. In the natural landscape, landforms and erosion rates follow the patterns expected for transient erosion along the mainstem, although a local base level lowering signal is not resolvable in many tributaries. Topographic relief, presence of knickpoints, and rock properties differ in the SFER tributaries. The tributaries draining mélange are over-steepened by boulders detached from hillslopes by earthflows. Here, we propose a framework in which rock properties and sediment size are a key control upon

Investigating the effect of key mutations on the conformational dynamics of toll-like receptor dimers through molecular dynamics simulations and protein structure networks.

PubMed

Mahita, Jarjapu; Sowdhamini, Ramanathan

2018-04-01

The Toll-like receptors (TLRs) are critical components of the innate immune system due to their ability to detect conserved pathogen-associated molecular patterns, present in bacteria, viruses, and other microorganisms. Ligand detection by TLRs leads to a signaling cascade, mediated by interactions among TIR domains present in the receptors, the bridging adaptors and sorting adaptors. The BB loop is a highly conserved region present in the TIR domain and is crucial for mediating interactions among TIR domain-containing proteins. Mutations in the BB loop of the Toll-like receptors, such as the A795P mutation in TLR3 and the P712H mutation (Lps d mutation) in TLR4, have been reported to disrupt or alter downstream signaling. While the phenotypic effect of these mutations is known, the underlying effect of these mutations on the structure, dynamics and interactions with other TIR domain-containing proteins is not well understood. Here, we have attempted to investigate the effect of the BB loop mutations on the dimer form of TLRs, using TLR2 and TLR3 as case studies. Our results based on molecular dynamics simulations, protein-protein interaction analyses and protein structure network analyses highlight significant differences between the dimer interfaces of the wild-type and mutant forms and provide a logical reasoning for the effect of these mutations on adaptor binding to TLRs. Furthermore, it also leads us to propose a hypothesis for the differential requirement of signaling and bridging adaptors by TLRs. This could aid in further understanding of the mechanisms governing such signaling pathways. © 2018 Wiley Periodicals, Inc.

A comparative study of cold- and warm-adapted Endonucleases A using sequence analyses and molecular dynamics simulations.

PubMed

Michetti, Davide; Brandsdal, Bjørn Olav; Bon, Davide; Isaksen, Geir Villy; Tiberti, Matteo; Papaleo, Elena

2017-01-01

The psychrophilic and mesophilic endonucleases A (EndA) from Aliivibrio salmonicida (VsEndA) and Vibrio cholera (VcEndA) have been studied experimentally in terms of the biophysical properties related to thermal adaptation. The analyses of their static X-ray structures was no sufficient to rationalize the determinants of their adaptive traits at the molecular level. Thus, we used Molecular Dynamics (MD) simulations to compare the two proteins and unveil their structural and dynamical differences. Our simulations did not show a substantial increase in flexibility in the cold-adapted variant on the nanosecond time scale. The only exception is a more rigid C-terminal region in VcEndA, which is ascribable to a cluster of electrostatic interactions and hydrogen bonds, as also supported by MD simulations of the VsEndA mutant variant where the cluster of interactions was introduced. Moreover, we identified three additional amino acidic substitutions through multiple sequence alignment and the analyses of MD-based protein structure networks. In particular, T120V occurs in the proximity of the catalytic residue H80 and alters the interaction with the residue Y43, which belongs to the second coordination sphere of the Mg2+ ion. This makes T120V an amenable candidate for future experimental mutagenesis.

Dynamical Analyses for Developmental Science: A Primer for Intrigued Scientists

ERIC Educational Resources Information Center

DiDonato, M. D.; England, D.; Martin, C. L.; Amazeen, P. G.

2013-01-01

Dynamical systems theory is becoming more popular in social and developmental science. However, unfamiliarity with dynamical analysis techniques remains an obstacle for developmentalists who would like to quantitatively apply dynamics in their own research. The goal of this article is to address this issue by clearly and simply presenting several…

Impact of Aging on the Dynamics of Memory Retrieval: A Time-Course Analysis

ERIC Educational Resources Information Center

Oztekin, Ilke; Gungor, Nur Zeynep; Badre, David

2012-01-01

The response-signal speed-accuracy trade-off (SAT) procedure was used to provide an in-depth investigation of the impact of aging on the dynamics of short-term memory retrieval. Young and older adults studied sequentially presented 3-item lists, immediately followed by a recognition probe. Analyses of composite list and serial position SAT…

Signal classification using global dynamical models, Part II: SONAR data analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kremliovsky, M.; Kadtke, J.

1996-06-01

In Part I of this paper, we described a numerical method for nonlinear signal detection and classification which made use of techniques borrowed from dynamical systems theory. Here in Part II of the paper, we will describe an example of data analysis using this method, for data consisting of open ocean acoustic (SONAR) recordings of marine mammal transients, supplied from NUWC sources. The purpose here is two-fold: first to give a more operational description of the technique and provide rules-of-thumb for parameter choices; and second to discuss some new issues raised by the analysis of non-ideal (real-world) data sets. Themore » particular data set considered here is quite non-stationary, relatively noisy, is not clearly localized in the background, and as such provides a difficult challenge for most detection/classification schemes. {copyright} {ital 1996 American Institute of Physics.}« less

Large-scale genomic analyses link reproductive aging to hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated DNA repair.

PubMed

Day, Felix R; Ruth, Katherine S; Thompson, Deborah J; Lunetta, Kathryn L; Pervjakova, Natalia; Chasman, Daniel I; Stolk, Lisette; Finucane, Hilary K; Sulem, Patrick; Bulik-Sullivan, Brendan; Esko, Tõnu; Johnson, Andrew D; Elks, Cathy E; Franceschini, Nora; He, Chunyan; Altmaier, Elisabeth; Brody, Jennifer A; Franke, Lude L; Huffman, Jennifer E; Keller, Margaux F; McArdle, Patrick F; Nutile, Teresa; Porcu, Eleonora; Robino, Antonietta; Rose, Lynda M; Schick, Ursula M; Smith, Jennifer A; Teumer, Alexander; Traglia, Michela; Vuckovic, Dragana; Yao, Jie; Zhao, Wei; Albrecht, Eva; Amin, Najaf; Corre, Tanguy; Hottenga, Jouke-Jan; Mangino, Massimo; Smith, Albert V; Tanaka, Toshiko; Abecasis, Goncalo; Andrulis, Irene L; Anton-Culver, Hoda; Antoniou, Antonis C; Arndt, Volker; Arnold, Alice M; Barbieri, Caterina; Beckmann, Matthias W; Beeghly-Fadiel, Alicia; Benitez, Javier; Bernstein, Leslie; Bielinski, Suzette J; Blomqvist, Carl; Boerwinkle, Eric; Bogdanova, Natalia V; Bojesen, Stig E; Bolla, Manjeet K; Borresen-Dale, Anne-Lise; Boutin, Thibaud S; Brauch, Hiltrud; Brenner, Hermann; Brüning, Thomas; Burwinkel, Barbara; Campbell, Archie; Campbell, Harry; Chanock, Stephen J; Chapman, J Ross; Chen, Yii-Der Ida; Chenevix-Trench, Georgia; Couch, Fergus J; Coviello, Andrea D; Cox, Angela; Czene, Kamila; Darabi, Hatef; De Vivo, Immaculata; Demerath, Ellen W; Dennis, Joe; Devilee, Peter; Dörk, Thilo; Dos-Santos-Silva, Isabel; Dunning, Alison M; Eicher, John D; Fasching, Peter A; Faul, Jessica D; Figueroa, Jonine; Flesch-Janys, Dieter; Gandin, Ilaria; Garcia, Melissa E; García-Closas, Montserrat; Giles, Graham G; Girotto, Giorgia G; Goldberg, Mark S; González-Neira, Anna; Goodarzi, Mark O; Grove, Megan L; Gudbjartsson, Daniel F; Guénel, Pascal; Guo, Xiuqing; Haiman, Christopher A; Hall, Per; Hamann, Ute; Henderson, Brian E; Hocking, Lynne J; Hofman, Albert; Homuth, Georg; Hooning, Maartje J; Hopper, John L; Hu, Frank B; Huang, Jinyan; Humphreys, Keith; Hunter, David J; Jakubowska, Anna; Jones, Samuel E; Kabisch, Maria; Karasik, David; Knight, Julia A; Kolcic, Ivana; Kooperberg, Charles; Kosma, Veli-Matti; Kriebel, Jennifer; Kristensen, Vessela; Lambrechts, Diether; Langenberg, Claudia; Li, Jingmei; Li, Xin; Lindström, Sara; Liu, Yongmei; Luan, Jian'an; Lubinski, Jan; Mägi, Reedik; Mannermaa, Arto; Manz, Judith; Margolin, Sara; Marten, Jonathan; Martin, Nicholas G; Masciullo, Corrado; Meindl, Alfons; Michailidou, Kyriaki; Mihailov, Evelin; Milani, Lili; Milne, Roger L; Müller-Nurasyid, Martina; Nalls, Michael; Neale, Ben M; Nevanlinna, Heli; Neven, Patrick; Newman, Anne B; Nordestgaard, Børge G; Olson, Janet E; Padmanabhan, Sandosh; Peterlongo, Paolo; Peters, Ulrike; Petersmann, Astrid; Peto, Julian; Pharoah, Paul D P; Pirastu, Nicola N; Pirie, Ailith; Pistis, Giorgio; Polasek, Ozren; Porteous, David; Psaty, Bruce M; Pylkäs, Katri; Radice, Paolo; Raffel, Leslie J; Rivadeneira, Fernando; Rudan, Igor; Rudolph, Anja; Ruggiero, Daniela; Sala, Cinzia F; Sanna, Serena; Sawyer, Elinor J; Schlessinger, David; Schmidt, Marjanka K; Schmidt, Frank; Schmutzler, Rita K; Schoemaker, Minouk J; Scott, Robert A; Seynaeve, Caroline M; Simard, Jacques; Sorice, Rossella; Southey, Melissa C; Stöckl, Doris; Strauch, Konstantin; Swerdlow, Anthony; Taylor, Kent D; Thorsteinsdottir, Unnur; Toland, Amanda E; Tomlinson, Ian; Truong, Thérèse; Tryggvadottir, Laufey; Turner, Stephen T; Vozzi, Diego; Wang, Qin; Wellons, Melissa; Willemsen, Gonneke; Wilson, James F; Winqvist, Robert; Wolffenbuttel, Bruce B H R; Wright, Alan F; Yannoukakos, Drakoulis; Zemunik, Tatijana; Zheng, Wei; Zygmunt, Marek; Bergmann, Sven; Boomsma, Dorret I; Buring, Julie E; Ferrucci, Luigi; Montgomery, Grant W; Gudnason, Vilmundur; Spector, Tim D; van Duijn, Cornelia M; Alizadeh, Behrooz Z; Ciullo, Marina; Crisponi, Laura; Easton, Douglas F; Gasparini, Paolo P; Gieger, Christian; Harris, Tamara B; Hayward, Caroline; Kardia, Sharon L R; Kraft, Peter; McKnight, Barbara; Metspalu, Andres; Morrison, Alanna C; Reiner, Alex P; Ridker, Paul M; Rotter, Jerome I; Toniolo, Daniela; Uitterlinden, André G; Ulivi, Sheila; Völzke, Henry; Wareham, Nicholas J; Weir, David R; Yerges-Armstrong, Laura M; Price, Alkes L; Stefansson, Kari; Visser, Jenny A; Ong, Ken K; Chang-Claude, Jenny; Murabito, Joanne M; Perry, John R B; Murray, Anna

2015-11-01

Menopause timing has a substantial impact on infertility and risk of disease, including breast cancer, but the underlying mechanisms are poorly understood. We report a dual strategy in ∼70,000 women to identify common and low-frequency protein-coding variation associated with age at natural menopause (ANM). We identified 44 regions with common variants, including two regions harboring additional rare missense alleles of large effect. We found enrichment of signals in or near genes involved in delayed puberty, highlighting the first molecular links between the onset and end of reproductive lifespan. Pathway analyses identified major association with DNA damage response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomization analyses supported a causal effect of later ANM on breast cancer risk (∼6% increase in risk per year; P = 3 × 10(-14)), likely mediated by prolonged sex hormone exposure rather than DDR mechanisms.

Large-scale genomic analyses link reproductive ageing to hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated DNA repair

PubMed Central

Lunetta, Kathryn L.; Pervjakova, Natalia; Chasman, Daniel I.; Stolk, Lisette; Finucane, Hilary K.; Sulem, Patrick; Bulik-Sullivan, Brendan; Esko, Tõnu; Johnson, Andrew D.; Elks, Cathy E.; Franceschini, Nora; He, Chunyan; Altmaier, Elisabeth; Brody, Jennifer A.; Franke, Lude L.; Huffman, Jennifer E.; Keller, Margaux F.; McArdle, Patrick F.; Nutile, Teresa; Porcu, Eleonora; Robino, Antonietta; Rose, Lynda M.; Schick, Ursula M.; Smith, Jennifer A.; Teumer, Alexander; Traglia, Michela; Vuckovic, Dragana; Yao, Jie; Zhao, Wei; Albrecht, Eva; Amin, Najaf; Corre, Tanguy; Hottenga, Jouke-Jan; Mangino, Massimo; Smith, Albert V.; Tanaka, Toshiko; Abecasis, Goncalo; Andrulis, Irene L.; Anton-Culver, Hoda; Antoniou, Antonis C.; Arndt, Volker; Arnold, Alice M.; Barbieri, Caterina; Beckmann, Matthias W.; Beeghly-Fadiel, Alicia; Benitez, Javier; Bernstein, Leslie; Bielinski, Suzette J.; Blomqvist, Carl; Boerwinkle, Eric; Bogdanova, Natalia V.; Bojesen, Stig E.; Bolla, Manjeet K.; Borresen-Dale, Anne-Lise; Boutin, Thibaud S; Brauch, Hiltrud; Brenner, Hermann; Brüning, Thomas; Burwinkel, Barbara; Campbell, Archie; Campbell, Harry; Chanock, Stephen J.; Chapman, J. Ross; Chen, Yii-Der Ida; Chenevix-Trench, Georgia; Couch, Fergus J.; Coviello, Andrea D.; Cox, Angela; Czene, Kamila; Darabi, Hatef; De Vivo, Immaculata; Demerath, Ellen W.; Dennis, Joe; Devilee, Peter; Dörk, Thilo; dos-Santos-Silva, Isabel; Dunning, Alison M.; Eicher, John D.; Fasching, Peter A.; Faul, Jessica D.; Figueroa, Jonine; Flesch-Janys, Dieter; Gandin, Ilaria; Garcia, Melissa E.; García-Closas, Montserrat; Giles, Graham G.; Girotto, Giorgia G.; Goldberg, Mark S.; González-Neira, Anna; Goodarzi, Mark O.; Grove, Megan L.; Gudbjartsson, Daniel F.; Guénel, Pascal; Guo, Xiuqing; Haiman, Christopher A.; Hall, Per; Hamann, Ute; Henderson, Brian E.; Hocking, Lynne J.; Hofman, Albert; Homuth, Georg; Hooning, Maartje J.; Hopper, John L.; Hu, Frank B.; Huang, Jinyan; Humphreys, Keith; Hunter, David J.; Jakubowska, Anna; Jones, Samuel E.; Kabisch, Maria; Karasik, David; Knight, Julia A.; Kolcic, Ivana; Kooperberg, Charles; Kosma, Veli-Matti; Kriebel, Jennifer; Kristensen, Vessela; Lambrechts, Diether; Langenberg, Claudia; Li, Jingmei; Li, Xin; Lindström, Sara; Liu, Yongmei; Luan, Jian’an; Lubinski, Jan; Mägi, Reedik; Mannermaa, Arto; Manz, Judith; Margolin, Sara; Marten, Jonathan; Martin, Nicholas G.; Masciullo, Corrado; Meindl, Alfons; Michailidou, Kyriaki; Mihailov, Evelin; Milani, Lili; Milne, Roger L.; Müller-Nurasyid, Martina; Nalls, Michael; Neale, Ben M.; Nevanlinna, Heli; Neven, Patrick; Newman, Anne B.; Nordestgaard, Børge G.; Olson, Janet E.; Padmanabhan, Sandosh; Peterlongo, Paolo; Peters, Ulrike; Petersmann, Astrid; Peto, Julian; Pharoah, Paul D.P.; Pirastu, Nicola N.; Pirie, Ailith; Pistis, Giorgio; Polasek, Ozren; Porteous, David; Psaty, Bruce M.; Pylkäs, Katri; Radice, Paolo; Raffel, Leslie J.; Rivadeneira, Fernando; Rudan, Igor; Rudolph, Anja; Ruggiero, Daniela; Sala, Cinzia F.; Sanna, Serena; Sawyer, Elinor J.; Schlessinger, David; Schmidt, Marjanka K.; Schmidt, Frank; Schmutzler, Rita K.; Schoemaker, Minouk J.; Scott, Robert A.; Seynaeve, Caroline M.; Simard, Jacques; Sorice, Rossella; Southey, Melissa C.; Stöckl, Doris; Strauch, Konstantin; Swerdlow, Anthony; Taylor, Kent D.; Thorsteinsdottir, Unnur; Toland, Amanda E.; Tomlinson, Ian; Truong, Thérèse; Tryggvadottir, Laufey; Turner, Stephen T.; Vozzi, Diego; Wang, Qin; Wellons, Melissa; Willemsen, Gonneke; Wilson, James F.; Winqvist, Robert; Wolffenbuttel, Bruce B.H.R.; Wright, Alan F.; Yannoukakos, Drakoulis; Zemunik, Tatijana; Zheng, Wei; Zygmunt, Marek; Bergmann, Sven; Boomsma, Dorret I.; Buring, Julie E.; Ferrucci, Luigi; Montgomery, Grant W.; Gudnason, Vilmundur; Spector, Tim D.; van Duijn, Cornelia M; Alizadeh, Behrooz Z.; Ciullo, Marina; Crisponi, Laura; Easton, Douglas F.; Gasparini, Paolo P.; Gieger, Christian; Harris, Tamara B.; Hayward, Caroline; Kardia, Sharon L.R.; Kraft, Peter; McKnight, Barbara; Metspalu, Andres; Morrison, Alanna C.; Reiner, Alex P.; Ridker, Paul M.; Rotter, Jerome I.; Toniolo, Daniela; Uitterlinden, André G.; Ulivi, Sheila; Völzke, Henry; Wareham, Nicholas J.; Weir, David R.; Yerges-Armstrong, Laura M.; Price, Alkes L.; Stefansson, Kari; Visser, Jenny A.; Ong, Ken K.; Chang-Claude, Jenny; Murabito, Joanne M.; Perry, John R.B.; Murray, Anna

2015-01-01

Menopause timing has a substantial impact on infertility and risk of disease, including breast cancer, but the underlying mechanisms are poorly understood. We report a dual strategy in ~70,000 women to identify common and low-frequency protein-coding variation associated with age at natural menopause (ANM). We identified 44 regions with common variants, including two harbouring additional rare missense alleles of large effect. We found enrichment of signals in/near genes involved in delayed puberty, highlighting the first molecular links between the onset and end of reproductive lifespan. Pathway analyses revealed a major association with DNA damage-response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomisation analyses supported a causal effect of later ANM on breast cancer risk (~6% risk increase per-year, P=3×10−14), likely mediated by prolonged sex hormone exposure, rather than DDR mechanisms. PMID:26414677

Phase-locking dynamics in optoelectronic oscillator

NASA Astrophysics Data System (ADS)

Banerjee, Abhijit; Sarkar, Jayjeet; Das, NikhilRanjan; Biswas, Baidyanath

2018-05-01

This paper analyzes the phase-locking phenomenon in single-loop optoelectronic microwave oscillators considering weak and strong radio frequency (RF) signal injection. The analyses are made in terms of the lock-range, beat frequency and the spectral components of the unlocked-driven oscillator. The influence of RF injection signal on the frequency pulling of the unlocked-driven optoelectronic oscillator (OEO) is also studied. An approximate expression for the amplitude perturbation of the oscillator is derived and the influence of amplitude perturbation on the phase-locking dynamics is studied. It is shown that the analysis clearly reveals the phase-locking phenomenon and the associated frequency pulling mechanism starting from the fast-beat state through the quasi-locked state to the locked state of the pulled OEO. It is found that the unlocked-driven OEO output signal has a very non-symmetrical sideband distribution about the carrier. The simulation results are also given in partial support to the conclusions of the analysis.

Hamiltonian model and dynamic analyses for a hydro-turbine governing system with fractional item and time-lag

NASA Astrophysics Data System (ADS)

Xu, Beibei; Chen, Diyi; Zhang, Hao; Wang, Feifei; Zhang, Xinguang; Wu, Yonghong

2017-06-01

This paper focus on a Hamiltonian mathematical modeling for a hydro-turbine governing system including fractional item and time-lag. With regards to hydraulic pressure servo system, a universal dynamical model is proposed, taking into account the viscoelastic properties and low-temperature impact toughness of constitutive materials as well as the occurrence of time-lag in the signal transmissions. The Hamiltonian model of the hydro-turbine governing system is presented using the method of orthogonal decomposition. Furthermore, a novel Hamiltonian function that provides more detailed energy information is presented, since the choice of the Hamiltonian function is the key issue by putting the whole dynamical system to the theory framework of the generalized Hamiltonian system. From the numerical experiments based on a real large hydropower station, we prove that the Hamiltonian function can describe the energy variation of the hydro-turbine suitably during operation. Moreover, the effect of the fractional α and the time-lag τ on the dynamic variables of the hydro-turbine governing system are explored and their change laws identified, respectively. The physical meaning between fractional calculus and time-lag are also discussed in nature. All of the above theories and numerical results are expected to provide a robust background for the safe operation and control of large hydropower stations.

Individual-Environment Interactions in Swimming: The Smallest Unit for Analysing the Emergence of Coordination Dynamics in Performance?

PubMed

Guignard, Brice; Rouard, Annie; Chollet, Didier; Hart, John; Davids, Keith; Seifert, Ludovic

2017-08-01

Displacement in competitive swimming is highly dependent on fluid characteristics, since athletes use these properties to propel themselves. It is essential for sport scientists and practitioners to clearly identify the interactions that emerge between each individual swimmer and properties of an aquatic environment. Traditionally, the two protagonists in these interactions have been studied separately. Determining the impact of each swimmer's movements on fluid flow, and vice versa, is a major challenge. Classic biomechanical research approaches have focused on swimmers' actions, decomposing stroke characteristics for analysis, without exploring perturbations to fluid flows. Conversely, fluid mechanics research has sought to record fluid behaviours, isolated from the constraints of competitive swimming environments (e.g. analyses in two-dimensions, fluid flows passively studied on mannequins or robot effectors). With improvements in technology, however, recent investigations have focused on the emergent circular couplings between swimmers' movements and fluid dynamics. Here, we provide insights into concepts and tools that can explain these on-going dynamic interactions in competitive swimming within the theoretical framework of ecological dynamics.

Nemo regulates cell dynamics and represses the expression of miple, a midkine/pleiotrophin cytokine, during ommatidial rotation

PubMed Central

Muñoz-Soriano, Verónica; Ruiz, Carlos; Pérez-Alonso, Manuel; Mlodzik, Marek; Paricio, Nuria

2013-01-01

Ommatidial rotation is one of the most important events for correct patterning of the Drosophila eye. Although several signaling pathways are involved in this process, few genes have been shown to specifically affect it. One of them is nemo (nmo), which encodes a MAP-like protein kinase that regulates the rate of rotation throughout the entire process, and serves as a link between core planar cell polarity (PCP) factors and the E-cadherin–β-catenin complex. To determine more precisely the role of nmo in ommatidial rotation, live-imaging analyses in nmo mutant and wild-type early pupal eye discs were performed. We demonstrate that ommatidial rotation is not a continuous process, and that rotating and non-rotating interommatidial cells are very dynamic. Our in vivo analyses also show that nmo regulates the speed of rotation and is required in cone cells for correct ommatidial rotation, and that these cells as well as interommatidial cells are less dynamic in nmo mutants. Furthermore, microarray analyses of nmo and wild-type larval eye discs led us to identify new genes and signaling pathways related to nmo function during this process. One of them, miple, encodes the Drosophila ortholog of the midkine/pleiotrophin secreted cytokines that are involved in cell migration processes. miple is highly up-regulated in nmo mutant discs. Indeed, phenotypic analyses reveal that miple overexpression leads to ommatidial rotation defects. Genetic interaction assays suggest that miple is signaling through Ptp99A, the Drosophila ortholog of the vertebrate midkine/pleiotrophin PTPζ receptor. Accordingly, we propose that one of the roles of Nmo during ommatial rotation is to repress miple expression, which may in turn affect the dynamics in E-cadherin–β-catenin complexes. PMID:23428616

Comprehensive analysis of the dynamic structure of nuclear localization signals.

PubMed

Yamagishi, Ryosuke; Okuyama, Takahide; Oba, Shuntaro; Shimada, Jiro; Chaen, Shigeru; Kaneko, Hiroki

2015-12-01

Most transcription and epigenetic factors in eukaryotic cells have nuclear localization signals (NLSs) and are transported to the nucleus by nuclear transport proteins. Understanding the features of NLSs and the mechanisms of nuclear transport might help understand gene expression regulation, somatic cell reprogramming, thus leading to the treatment of diseases associated with abnormal gene expression. Although many studies analyzed the amino acid sequence of NLSs, few studies investigated their three-dimensional structure. Therefore, we conducted a statistical investigation of the dynamic structure of NLSs by extracting the conformation of these sequences from proteins examined by X-ray crystallography and using a quantity defined as conformational determination rate (a ratio between the number of amino acids determining the conformation and the number of all amino acids included in a certain region). We found that determining the conformation of NLSs is more difficult than determining the conformation of other regions and that NLSs may tend to form more heteropolymers than monomers. Therefore, these findings strongly suggest that NLSs are intrinsically disordered regions.

Spatial dynamics of action potentials estimated by dendritic Ca(2+) signals in insect projection neurons.

PubMed

Ogawa, Hiroto; Mitani, Ruriko

2015-11-13

The spatial dynamics of action potentials, including their propagation and the location of spike initiation zone (SIZ), are crucial for the computation of a single neuron. Compared with mammalian central neurons, the spike dynamics of invertebrate neurons remain relatively unknown. Thus, we examined the spike dynamics based on single spike-induced Ca(2+) signals in the dendrites of cricket mechanosensory projection neurons, known as giant interneurons (GIs). The Ca(2+) transients induced by a synaptically evoked single spike were larger than those induced by an antidromic spike, whereas subthreshold synaptic potentials caused no elevation of Ca(2+). These results indicate that synaptic activity enhances the dendritic Ca(2+) influx through voltage-gated Ca(2+) channels. Stimulation of the presynaptic sensory afferents ipsilateral to the recording site evoked a dendritic spike with higher amplitude than contralateral stimulation, thereby suggesting that alteration of the spike waveform resulted in synaptic enhancement of the dendritic Ca(2+) transients. The SIZ estimated from the spatial distribution of the difference in the Ca(2+) amplitude was distributed throughout the right and left dendritic branches across the primary neurite connecting them in GIs. Copyright © 2015 Elsevier Inc. All rights reserved.

A Robust Dynamic Heart-Rate Detection Algorithm Framework During Intense Physical Activities Using Photoplethysmographic Signals

PubMed Central

Song, Jiajia; Li, Dan; Ma, Xiaoyuan; Teng, Guowei; Wei, Jianming

2017-01-01

Dynamic accurate heart-rate (HR) estimation using a photoplethysmogram (PPG) during intense physical activities is always challenging due to corruption by motion artifacts (MAs). It is difficult to reconstruct a clean signal and extract HR from contaminated PPG. This paper proposes a robust HR-estimation algorithm framework that uses one-channel PPG and tri-axis acceleration data to reconstruct the PPG and calculate the HR based on features of the PPG and spectral analysis. Firstly, the signal is judged by the presence of MAs. Then, the spectral peaks corresponding to acceleration data are filtered from the periodogram of the PPG when MAs exist. Different signal-processing methods are applied based on the amount of remaining PPG spectral peaks. The main MA-removal algorithm (NFEEMD) includes the repeated single-notch filter and ensemble empirical mode decomposition. Finally, HR calibration is designed to ensure the accuracy of HR tracking. The NFEEMD algorithm was performed on the 23 datasets from the 2015 IEEE Signal Processing Cup Database. The average estimation errors were 1.12 BPM (12 training datasets), 2.63 BPM (10 testing datasets) and 1.87 BPM (all 23 datasets), respectively. The Pearson correlation was 0.992. The experiment results illustrate that the proposed algorithm is not only suitable for HR estimation during continuous activities, like slow running (13 training datasets), but also for intense physical activities with acceleration, like arm exercise (10 testing datasets). PMID:29068403

Use of restrained molecular dynamics to predict the conformations of phosphorylated receiver domains in two-component signaling systems.

PubMed

Foster, Clay A; West, Ann H

2017-01-01

Two-component signaling (TCS) is the primary means by which bacteria, as well as certain plants and fungi, respond to external stimuli. Signal transduction involves stimulus-dependent autophosphorylation of a sensor histidine kinase and phosphoryl transfer to the receiver domain of a downstream response regulator. Phosphorylation acts as an allosteric switch, inducing structural and functional changes in the pathway's components. Due to their transient nature, phosphorylated receiver domains are challenging to characterize structurally. In this work, we provide a methodology for simulating receiver domain phosphorylation to predict conformations that are nearly identical to experimental structures. Using restrained molecular dynamics, phosphorylated conformations of receiver domains can be reliably sampled on nanosecond timescales. These simulations also provide data on conformational dynamics that can be used to identify regions of functional significance related to phosphorylation. We first validated this approach on several well-characterized receiver domains and then used it to compare the upstream and downstream components of the fungal Sln1 phosphorelay. Our results demonstrate that this technique provides structural insight, obtained in the absence of crystallographic or NMR information, regarding phosphorylation-induced conformational changes in receiver domains that regulate the output of their associated signaling pathway. To our knowledge, this is the first time such a protocol has been described that can be broadly applied to TCS proteins for predictive purposes. Proteins 2016; 85:155-176. © 2016 Wiley Periodicals, Inc. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

Dynamic Interaction- and Phospho-Proteomics Reveal Lck as a Major Signaling Hub of CD147 in T Cells.

PubMed

Supper, Verena; Hartl, Ingrid; Boulègue, Cyril; Ohradanova-Repic, Anna; Stockinger, Hannes

2017-03-15

Numerous publications have addressed CD147 as a tumor marker and regulator of cytoskeleton, cell growth, stress response, or immune cell function; however, the molecular functionality of CD147 remains incompletely understood. Using affinity purification, mass spectrometry, and phosphopeptide enrichment of isotope-labeled peptides, we examined the dynamic of the CD147 microenvironment and the CD147-dependent phosphoproteome in the Jurkat T cell line upon treatment with T cell stimulating agents. We identified novel dynamic interaction partners of CD147 such as CD45, CD47, GNAI2, Lck, RAP1B, and VAT1 and, furthermore, found 76 CD147-dependent phosphorylation sites on 57 proteins. Using the STRING protein network database, a network between the CD147 microenvironment and the CD147-dependent phosphoproteins was generated and led to the identification of key signaling hubs around the G proteins RAP1B and GNB1, the kinases PKCβ, PAK2, Lck, and CDK1, and the chaperone HSPA5. Gene ontology biological process term analysis revealed that wound healing-, cytoskeleton-, immune system-, stress response-, phosphorylation- and protein modification-, defense response to virus-, and TNF production-associated terms are enriched within the microenvironment and the phosphoproteins of CD147. With the generated signaling network and gene ontology biological process term grouping, we identify potential signaling routes of CD147 affecting T cell growth and function. Copyright © 2017 by The American Association of Immunologists, Inc.

Dynamic Cross-Entropy.

PubMed

Aur, Dorian; Vila-Rodriguez, Fidel

2017-01-01

Complexity measures for time series have been used in many applications to quantify the regularity of one dimensional time series, however many dynamical systems are spatially distributed multidimensional systems. We introduced Dynamic Cross-Entropy (DCE) a novel multidimensional complexity measure that quantifies the degree of regularity of EEG signals in selected frequency bands. Time series generated by discrete logistic equations with varying control parameter r are used to test DCE measures. Sliding window DCE analyses are able to reveal specific period doubling bifurcations that lead to chaos. A similar behavior can be observed in seizures triggered by electroconvulsive therapy (ECT). Sample entropy data show the level of signal complexity in different phases of the ictal ECT. The transition to irregular activity is preceded by the occurrence of cyclic regular behavior. A significant increase of DCE values in successive order from high frequencies in gamma to low frequencies in delta band reveals several phase transitions into less ordered states, possible chaos in the human brain. To our knowledge there are no reliable techniques able to reveal the transition to chaos in case of multidimensional times series. In addition, DCE based on sample entropy appears to be robust to EEG artifacts compared to DCE based on Shannon entropy. The applied technique may offer new approaches to better understand nonlinear brain activity. Copyright © 2016 Elsevier B.V. All rights reserved.

Low-Rank and Adaptive Sparse Signal (LASSI) Models for Highly Accelerated Dynamic Imaging.

PubMed

Ravishankar, Saiprasad; Moore, Brian E; Nadakuditi, Raj Rao; Fessler, Jeffrey A

2017-05-01

Sparsity-based approaches have been popular in many applications in image processing and imaging. Compressed sensing exploits the sparsity of images in a transform domain or dictionary to improve image recovery fromundersampledmeasurements. In the context of inverse problems in dynamic imaging, recent research has demonstrated the promise of sparsity and low-rank techniques. For example, the patches of the underlying data are modeled as sparse in an adaptive dictionary domain, and the resulting image and dictionary estimation from undersampled measurements is called dictionary-blind compressed sensing, or the dynamic image sequence is modeled as a sum of low-rank and sparse (in some transform domain) components (L+S model) that are estimated from limited measurements. In this work, we investigate a data-adaptive extension of the L+S model, dubbed LASSI, where the temporal image sequence is decomposed into a low-rank component and a component whose spatiotemporal (3D) patches are sparse in some adaptive dictionary domain. We investigate various formulations and efficient methods for jointly estimating the underlying dynamic signal components and the spatiotemporal dictionary from limited measurements. We also obtain efficient sparsity penalized dictionary-blind compressed sensing methods as special cases of our LASSI approaches. Our numerical experiments demonstrate the promising performance of LASSI schemes for dynamicmagnetic resonance image reconstruction from limited k-t space data compared to recent methods such as k-t SLR and L+S, and compared to the proposed dictionary-blind compressed sensing method.

Parameter space exploration within dynamic simulations of signaling networks.

PubMed

De Ambrosi, Cristina; Barla, Annalisa; Tortolina, Lorenzo; Castagnino, Nicoletta; Pesenti, Raffaele; Verri, Alessandro; Ballestrero, Alberto; Patrone, Franco; Parodi, Silvio

2013-02-01

We started offering an introduction to very basic aspects of molecular biology, for the reader coming from computer sciences, information technology, mathematics. Similarly we offered a minimum of information about pathways and networks in graph theory, for a reader coming from the bio-medical sector. At the crossover about the two different types of expertise, we offered some definition about Systems Biology. The core of the article deals with a Molecular Interaction Map (MIM), a network of biochemical interactions involved in a small signaling-network sub-region relevant in breast cancer. We explored robustness/sensitivity to random perturbations. It turns out that our MIM is a non-isomorphic directed graph. For non physiological directions of propagation of the signal the network is quite resistant to perturbations. The opposite happens for biologically significant directions of signal propagation. In these cases we can have no signal attenuation, and even signal amplification. Signal propagation along a given pathway is highly unidirectional, with the exception of signal-feedbacks, that again have a specific biological role and significance. In conclusion, even a relatively small network like our present MIM reveals the preponderance of specific biological functions over unspecific isomorphic behaviors. This is perhaps the consequence of hundreds of millions of years of biological evolution.

Systematic parameter estimation in data-rich environments for cell signalling dynamics

PubMed Central

Nim, Tri Hieu; Luo, Le; Clément, Marie-Véronique; White, Jacob K.; Tucker-Kellogg, Lisa

2013-01-01

Motivation: Computational models of biological signalling networks, based on ordinary differential equations (ODEs), have generated many insights into cellular dynamics, but the model-building process typically requires estimating rate parameters based on experimentally observed concentrations. New proteomic methods can measure concentrations for all molecular species in a pathway; this creates a new opportunity to decompose the optimization of rate parameters. Results: In contrast with conventional parameter estimation methods that minimize the disagreement between simulated and observed concentrations, the SPEDRE method fits spline curves through observed concentration points, estimates derivatives and then matches the derivatives to the production and consumption of each species. This reformulation of the problem permits an extreme decomposition of the high-dimensional optimization into a product of low-dimensional factors, each factor enforcing the equality of one ODE at one time slice. Coarsely discretized solutions to the factors can be computed systematically. Then the discrete solutions are combined using loopy belief propagation, and refined using local optimization. SPEDRE has unique asymptotic behaviour with runtime polynomial in the number of molecules and timepoints, but exponential in the degree of the biochemical network. SPEDRE performance is comparatively evaluated on a novel model of Akt activation dynamics including redox-mediated inactivation of PTEN (phosphatase and tensin homologue). Availability and implementation: Web service, software and supplementary information are available at www.LtkLab.org/SPEDRE Supplementary information: Supplementary data are available at Bioinformatics online. Contact: LisaTK@nus.edu.sg PMID:23426255

Phase synchronization of instrumental music signals

NASA Astrophysics Data System (ADS)

Mukherjee, Sayan; Palit, Sanjay Kumar; Banerjee, Santo; Ariffin, M. R. K.; Bhattacharya, D. K.

2014-06-01

Signal analysis is one of the finest scientific techniques in communication theory. Some quantitative and qualitative measures describe the pattern of a music signal, vary from one to another. Same musical recital, when played by different instrumentalists, generates different types of music patterns. The reason behind various patterns is the psycho-acoustic measures - Dynamics, Timber, Tonality and Rhythm, varies in each time. However, the psycho-acoustic study of the music signals does not reveal any idea about the similarity between the signals. For such cases, study of synchronization of long-term nonlinear dynamics may provide effective results. In this context, phase synchronization (PS) is one of the measures to show synchronization between two non-identical signals. In fact, it is very critical to investigate any other kind of synchronization for experimental condition, because those are completely non identical signals. Also, there exists equivalence between the phases and the distances of the diagonal line in Recurrence plot (RP) of the signals, which is quantifiable by the recurrence quantification measure τ-recurrence rate. This paper considers two nonlinear music signals based on same raga played by two eminent sitar instrumentalists as two non-identical sources. The psycho-acoustic study shows how the Dynamics, Timber, Tonality and Rhythm vary for the two music signals. Then, long term analysis in the form of phase space reconstruction is performed, which reveals the chaotic phase spaces for both the signals. From the RP of both the phase spaces, τ-recurrence rate is calculated. Finally by the correlation of normalized tau-recurrence rate of their 3D phase spaces and the PS of the two music signals has been established. The numerical results well support the analysis.

A Dynamic Stimulus-Driven Model of Signal Detection

ERIC Educational Resources Information Center

Turner, Brandon M.; Van Zandt, Trisha; Brown, Scott

2011-01-01

Signal detection theory forms the core of many current models of cognition, including memory, choice, and categorization. However, the classic signal detection model presumes the a priori existence of fixed stimulus representations--usually Gaussian distributions--even when the observer has no experience with the task. Furthermore, the classic…

Automated headspace solid-phase dynamic extraction to analyse the volatile fraction of food matrices.

PubMed

Bicchi, Carlo; Cordero, Chiara; Liberto, Erica; Rubiolo, Patrizia; Sgorbini, Barbara

2004-01-23

High concentration capacity headspace techniques (headspace solid-phase microextraction (HS-SPME) and headspace sorptive extraction (HSSE)) are a bridge between static and dynamic headspace, since they give high concentration factors as does dynamic headspace (D-HS), and are as easy to apply and as reproducible as static headspace (S-HS). In 2000, Chromtech (Idstein, Germany) introduced an inside-needle technique for vapour and liquid sampling, solid-phase dynamic extraction (SPDE), also known as "the magic needle". In SPDE, analytes are concentrated on a 50 microm film of polydimethylsiloxane (PDMS) and activated carbon (10%) coated onto the inside wall of the stainless steel needle (5 cm) of a 2.5 ml gas tight syringe. When SPDE is used for headspace sampling (HS-SPDE), a fixed volume of the headspace of the sample under investigation is sucked up an appropriate number of times with the gas tight syringe and an analyte amount suitable for a reliable GC or GC-MS analysis accumulates in the polymer coating the needle wall. This article describes the preliminary results of both a study on the optimisation of sampling parameters conditioning HS-SPDE recovery, through the analysis of a standard mixture of highly volatile compounds (beta-pinene, isoamyl acetate and linalool) and of the HS-SPDE-GC-MS analyses of aromatic plants and food matrices. This study shows that HS-SPDE is a successful technique for HS-sampling with high concentration capability, good repeatability and intermediate precision, also when it is compared to HS-SPME.

Rho GTPases at the crossroad of signaling networks in mammals: impact of Rho-GTPases on microtubule organization and dynamics.

PubMed

Wojnacki, José; Quassollo, Gonzalo; Marzolo, María-Paz; Cáceres, Alfredo

2014-01-01

Microtubule (MT) organization and dynamics downstream of external cues is crucial for maintaining cellular architecture and the generation of cell asymmetries. In interphase cells RhoA, Rac, and Cdc42, conspicuous members of the family of small Rho GTPases, have major roles in modulating MT stability, and hence polarized cell behaviors. However, MTs are not mere targets of Rho GTPases, but also serve as signaling platforms coupling MT dynamics to Rho GTPase activation in a variety of cellular conditions. In this article, we review some of the key studies describing the reciprocal relationship between small Rho-GTPases and MTs during migration and polarization.

Inverse Modelling to Obtain Head Movement Controller Signal

NASA Technical Reports Server (NTRS)

Kim, W. S.; Lee, S. H.; Hannaford, B.; Stark, L.

1984-01-01

Experimentally obtained dynamics of time-optimal, horizontal head rotations have previously been simulated by a sixth order, nonlinear model driven by rectangular control signals. Electromyography (EMG) recordings have spects which differ in detail from the theoretical rectangular pulsed control signal. Control signals for time-optimal as well as sub-optimal horizontal head rotations were obtained by means of an inverse modelling procedures. With experimentally measured dynamical data serving as the input, this procedure inverts the model to produce the neurological control signals driving muscles and plant. The relationships between these controller signals, and EMG records should contribute to the understanding of the neurological control of movements.

SU-E-J-261: Statistical Analysis and Chaotic Dynamics of Respiratory Signal of Patients in BodyFix

DOE Office of Scientific and Technical Information (OSTI.GOV)

Michalski, D; Huq, M; Bednarz, G

Purpose: To quantify respiratory signal of patients in BodyFix undergoing 4DCT scan with and without immobilization cover. Methods: 20 pairs of respiratory tracks recorded with RPM system during 4DCT scan were analyzed. Descriptive statistic was applied to selected parameters of exhale-inhale decomposition. Standardized signals were used with the delay method to build orbits in embedded space. Nonlinear behavior was tested with surrogate data. Sample entropy SE, Lempel-Ziv complexity LZC and the largest Lyapunov exponents LLE were compared. Results: Statistical tests show difference between scans for inspiration time and its variability, which is bigger for scans without cover. The same ismore » for variability of the end of exhalation and inhalation. Other parameters fail to show the difference. For both scans respiratory signals show determinism and nonlinear stationarity. Statistical test on surrogate data reveals their nonlinearity. LLEs show signals chaotic nature and its correlation with breathing period and its embedding delay time. SE, LZC and LLE measure respiratory signal complexity. Nonlinear characteristics do not differ between scans. Conclusion: Contrary to expectation cover applied to patients in BodyFix appears to have limited effect on signal parameters. Analysis based on trajectories of delay vectors shows respiratory system nonlinear character and its sensitive dependence on initial conditions. Reproducibility of respiratory signal can be evaluated with measures of signal complexity and its predictability window. Longer respiratory period is conducive for signal reproducibility as shown by these gauges. Statistical independence of the exhale and inhale times is also supported by the magnitude of LLE. The nonlinear parameters seem more appropriate to gauge respiratory signal complexity since its deterministic chaotic nature. It contrasts with measures based on harmonic analysis that are blind for nonlinear features. Dynamics of breathing, so

Signalling networks and dynamics of allosteric transitions in bacterial chaperonin GroEL: implications for iterative annealing of misfolded proteins.

PubMed

Thirumalai, D; Hyeon, Changbong

2018-06-19

Signal transmission at the molecular level in many biological complexes occurs through allosteric transitions. Allostery describes the responses of a complex to binding of ligands at sites that are spatially well separated from the binding region. We describe the structural perturbation method, based on phonon propagation in solids, which can be used to determine the signal-transmitting allostery wiring diagram (AWD) in large but finite-sized biological complexes. Application to the bacterial chaperonin GroEL-GroES complex shows that the AWD determined from structures also drives the allosteric transitions dynamically. From both a structural and dynamical perspective these transitions are largely determined by formation and rupture of salt-bridges. The molecular description of allostery in GroEL provides insights into its function, which is quantitatively described by the iterative annealing mechanism. Remarkably, in this complex molecular machine, a deep connection is established between the structures, reaction cycle during which GroEL undergoes a sequence of allosteric transitions, and function, in a self-consistent manner.This article is part of a discussion meeting issue 'Allostery and molecular machines'. © 2018 The Author(s).

A review of signals used in sleep analysis

PubMed Central

Roebuck, A; Monasterio, V; Gederi, E; Osipov, M; Behar, J; Malhotra, A; Penzel, T; Clifford, GD

2014-01-01

This article presents a review of signals used for measuring physiology and activity during sleep and techniques for extracting information from these signals. We examine both clinical needs and biomedical signal processing approaches across a range of sensor types. Issues with recording and analysing the signals are discussed, together with their applicability to various clinical disorders. Both univariate and data fusion (exploiting the diverse characteristics of the primary recorded signals) approaches are discussed, together with a comparison of automated methods for analysing sleep. PMID:24346125

Functional connectivity change as shared signal dynamics

PubMed Central

Cole, Michael W.; Yang, Genevieve J.; Murray, John D.; Repovš, Grega; Anticevic, Alan

2015-01-01

Background An increasing number of neuroscientific studies gain insights by focusing on differences in functional connectivity – between groups, individuals, temporal windows, or task conditions. We found using simulations that additional insights into such differences can be gained by forgoing variance normalization, a procedure used by most functional connectivity measures. Simulations indicated that these functional connectivity measures are sensitive to increases in independent fluctuations (unshared signal) in time series, consistently reducing functional connectivity estimates (e.g., correlations) even though such changes are unrelated to corresponding fluctuations (shared signal) between those time series. This is inconsistent with the common notion of functional connectivity as the amount of inter-region interaction. New Method Simulations revealed that a version of correlation without variance normalization – covariance – was able to isolate differences in shared signal, increasing interpretability of observed functional connectivity change. Simulations also revealed cases problematic for non-normalized methods, leading to a “covariance conjunction” method combining the benefits of both normalized and non-normalized approaches. Results We found that covariance and covariance conjunction methods can detect functional connectivity changes across a variety of tasks and rest in both clinical and non-clinical functional MRI datasets. Comparison with Existing Method(s) We verified using a variety of tasks and rest in both clinical and non-clinical functional MRI datasets that it matters in practice whether correlation, covariance, or covariance conjunction methods are used. Conclusions These results demonstrate the practical and theoretical utility of isolating changes in shared signal, improving the ability to interpret observed functional connectivity change. PMID:26642966

Functional dynamics of cell surface membrane proteins

NASA Astrophysics Data System (ADS)

Nishida, Noritaka; Osawa, Masanori; Takeuchi, Koh; Imai, Shunsuke; Stampoulis, Pavlos; Kofuku, Yutaka; Ueda, Takumi; Shimada, Ichio

2014-04-01

Cell surface receptors are integral membrane proteins that receive external stimuli, and transmit signals across plasma membranes. In the conventional view of receptor activation, ligand binding to the extracellular side of the receptor induces conformational changes, which convert the structure of the receptor into an active conformation. However, recent NMR studies of cell surface membrane proteins have revealed that their structures are more dynamic than previously envisioned, and they fluctuate between multiple conformations in an equilibrium on various timescales. In addition, NMR analyses, along with biochemical and cell biological experiments indicated that such dynamical properties are critical for the proper functions of the receptors. In this review, we will describe several NMR studies that revealed direct linkage between the structural dynamics and the functions of the cell surface membrane proteins, such as G-protein coupled receptors (GPCRs), ion channels, membrane transporters, and cell adhesion molecules.

Molecular Dynamics Underlie the Nature of MRI Signals: The NMR Shutter-Speed

NASA Astrophysics Data System (ADS)

Springer, Charles S., Jr.

2007-03-01

Motions of the spin-bearing molecules can have profound effects on the very nature (the exponentiality) of the macroscopic NMR signal. Quantitative mechanistic protocols often involve varying the equilibrium molecular kinetics (usually by temperature change) relative to the ``NMR time-scale'' (SS-1), usually ill-defined as the absolute difference of resonance frequencies [|δφ|] in sites between which spins are exchanged. This holds true for the equilibrium water molecule exchange between tissue compartments and distinct populations. However, in vivo studies must [by regulation] be isothermal, and the tissue ^1H2O MRI signals remain essentially isochronous [δφ = 0]. In NMR, an equilibrium process is manifest in the context of its ``exchange condition.'' It only ``appears'' to be fast or slow by comparison of its actual rate constant with its system ``shutter-speed'' (SS). [A nonzero δφ is the first, but not only, SS: its dimension is reciprocal time.] The process kinetics can be measured only if its NMR condition is varied at least partway between the fast- and slow exchange limits. In an isothermal study with no catalyst, this can be accomplished only by varying the pertinent SS. An MRI contrast reagent (CR) increases the laboratory frame ^1H2O relaxation rate constant, Ri [≡ (Ti)-1; i = 1,2]. For an isochronous exchange process, the SS is the intrinsic |δRi| for the sites. In quantitative dynamic-contrast-enhanced (DCE) studies, analytical pharmacokinetic modeling is accomplished on region-of-interest (ROI) or pixel by pixel ^1H2O signal time-courses following bolus CR injections. Accounting for the equilibrium transendothelial and transcytolemmal water interchange processes (a three-site exchange situation) is crucial for modeling accuracy: the relevant SS values vary during the CR bolus passage. This is so for DCE studies of cancer, multiple sclerosis, and myocardial blood flow variation. It is necessary for the successful discrimination of malignant

Equation of State Dependent Dynamics and Multi-messenger Signals from Stellar-mass Black Hole Formation

NASA Astrophysics Data System (ADS)

Pan, Kuo-Chuan; Liebendörfer, Matthias; Couch, Sean M.; Thielemann, Friedrich-Karl

2018-04-01

We investigate axisymmetric black hole (BH) formation and its gravitational wave (GW) and neutrino signals with self-consistent core-collapse supernova simulations of a non-rotating 40 M ⊙ progenitor star using the isotropic diffusion source approximation for the neutrino transport and a modified gravitational potential for general relativistic effects. We consider four different neutron star (NS) equations of state (EoS): LS220, SFHo, BHBΛϕ, and DD2, and study the impact of the EoS on BH formation dynamics and GW emission. We find that the BH formation time is sensitive to the EoS from 460 to >1300 ms and is delayed in multiple dimensions for ∼100–250 ms due to the finite entropy effects. Depending on the EoS, our simulations show the possibility that shock revival can occur along with the collapse of the proto-neutron star (PNS) to a BH. The gravitational waveforms contain four major features that are similar to previous studies but show extreme values: (1) a low-frequency signal (∼300–500 Hz) from core-bounce and prompt convection, (2) a strong signal from the PNS g-mode oscillation among other features, (3) a high-frequency signal from the PNS inner-core convection, and (4) signals from the standing accretion shock instability and convection. The peak frequency at the onset of BH formation reaches to ∼2.3 kHz. The characteristic amplitude of a 10 kpc object at peak frequency is detectable but close to the noise threshold of the Advanced LIGO and KAGRA, suggesting that the next-generation GW detector will need to improve the sensitivity at the kHz domain to better observe stellar-mass BH formation from core-collapse supernovae or failed supernovae.

SPICODYN: A Toolbox for the Analysis of Neuronal Network Dynamics and Connectivity from Multi-Site Spike Signal Recordings.

PubMed

Pastore, Vito Paolo; Godjoski, Aleksandar; Martinoia, Sergio; Massobrio, Paolo

2018-01-01

We implemented an automated and efficient open-source software for the analysis of multi-site neuronal spike signals. The software package, named SPICODYN, has been developed as a standalone windows GUI application, using C# programming language with Microsoft Visual Studio based on .NET framework 4.5 development environment. Accepted input data formats are HDF5, level 5 MAT and text files, containing recorded or generated time series spike signals data. SPICODYN processes such electrophysiological signals focusing on: spiking and bursting dynamics and functional-effective connectivity analysis. In particular, for inferring network connectivity, a new implementation of the transfer entropy method is presented dealing with multiple time delays (temporal extension) and with multiple binary patterns (high order extension). SPICODYN is specifically tailored to process data coming from different Multi-Electrode Arrays setups, guarantying, in those specific cases, automated processing. The optimized implementation of the Delayed Transfer Entropy and the High-Order Transfer Entropy algorithms, allows performing accurate and rapid analysis on multiple spike trains from thousands of electrodes.

Thermo-elastic wave model of the photothermal and photoacoustic signal

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meja, P.; Steiger, B.; Delsanto, P.P.

1996-12-31

By means of the thermo-elastic wave equation the dynamical propagation of mechanical stress and temperature can be described and applied to model the photothermal and photoacoustic signal. Analytical solutions exist only in particular cases. Using massively parallel computers it is possible to simulate the photothermal and photoacoustic signal in a most sufficient way. In this paper the method of local interaction simulation approach (LISA) is presented and selected examples of its application are given. The advantages of this method, which is particularly suitable for parallel processing, consist in reduced computation time and simple description of the photoacoustic signal in opticalmore » materials. The present contribution introduces the authors model, the formalism and some results in the 1 D case for homogeneous nonattenuative materials. The photoacoustic wave can be understood as a wave with locally limited displacement. This displacement corresponds to a temperature variation. Both variables are usually measured in photoacoustics and photothermal measurements. Therefore the temperature and displacement dependence on optical, elastic and thermal constants is analysed.« less

Dynamic Receptor Team Formation Can Explain the High Signal Transduction Gain in Escherichia coli

PubMed Central

Albert, Réka; Chiu, Yu-wen; Othmer, Hans G.

2004-01-01

Evolution has provided many organisms with sophisticated sensory systems that enable them to respond to signals in their environment. The response frequently involves alteration in the pattern of movement, either by directed movement, a process called taxis, or by altering the speed or frequency of turning, which is called kinesis. Chemokinesis has been most thoroughly studied in the peritrichous bacterium Escherichia coli, which has four helical flagella distributed over the cell surface, and swims by rotating them. When rotated counterclockwise the flagella coalesce into a propulsive bundle, producing a relatively straight “run,” and when rotated clockwise they fly apart, resulting in a “tumble” which reorients the cell with little translocation. A stochastic process generates the runs and tumbles, and in a chemoeffector gradient, runs that carry the cell in a favorable direction are extended. The cell senses spatial gradients as temporal changes in receptor occupancy and changes the probability of counterclockwise rotation (the bias) on a fast timescale, but adaptation returns the bias to baseline on a slow timescale, enabling the cell to detect and respond to further concentration changes. The overall structure of the signal transduction pathways is well characterized in E. coli, but important details are still not understood. Only recently has a source of gain in the signal transduction network been identified experimentally, and here we present a mathematical model based on dynamic assembly of receptor teams that can explain this observation. PMID:15111386

Dynamic receptor team formation can explain the high signal transduction gain in Escherichia coli.

PubMed

Albert, Réka; Chiu, Yu-Wen; Othmer, Hans G

2004-05-01

Evolution has provided many organisms with sophisticated sensory systems that enable them to respond to signals in their environment. The response frequently involves alteration in the pattern of movement, either by directed movement, a process called taxis, or by altering the speed or frequency of turning, which is called kinesis. Chemokinesis has been most thoroughly studied in the peritrichous bacterium Escherichia coli, which has four helical flagella distributed over the cell surface, and swims by rotating them. When rotated counterclockwise the flagella coalesce into a propulsive bundle, producing a relatively straight "run," and when rotated clockwise they fly apart, resulting in a "tumble" which reorients the cell with little translocation. A stochastic process generates the runs and tumbles, and in a chemoeffector gradient, runs that carry the cell in a favorable direction are extended. The cell senses spatial gradients as temporal changes in receptor occupancy and changes the probability of counterclockwise rotation (the bias) on a fast timescale, but adaptation returns the bias to baseline on a slow timescale, enabling the cell to detect and respond to further concentration changes. The overall structure of the signal transduction pathways is well characterized in E. coli, but important details are still not understood. Only recently has a source of gain in the signal transduction network been identified experimentally, and here we present a mathematical model based on dynamic assembly of receptor teams that can explain this observation.

Optimized lighting method of applying shaped-function signal for increasing the dynamic range of LED-multispectral imaging system

NASA Astrophysics Data System (ADS)

Yang, Xue; Hu, Yajia; Li, Gang; Lin, Ling

2018-02-01

This paper proposes an optimized lighting method of applying a shaped-function signal for increasing the dynamic range of light emitting diode (LED)-multispectral imaging system. The optimized lighting method is based on the linear response zone of the analog-to-digital conversion (ADC) and the spectral response of the camera. The auxiliary light at a higher sensitivity-camera area is introduced to increase the A/D quantization levels that are within the linear response zone of ADC and improve the signal-to-noise ratio. The active light is modulated by the shaped-function signal to improve the gray-scale resolution of the image. And the auxiliary light is modulated by the constant intensity signal, which is easy to acquire the images under the active light irradiation. The least square method is employed to precisely extract the desired images. One wavelength in multispectral imaging based on LED illumination was taken as an example. It has been proven by experiments that the gray-scale resolution and the accuracy of information of the images acquired by the proposed method were both significantly improved. The optimum method opens up avenues for the hyperspectral imaging of biological tissue.

Optimized lighting method of applying shaped-function signal for increasing the dynamic range of LED-multispectral imaging system.

PubMed

Yang, Xue; Hu, Yajia; Li, Gang; Lin, Ling

2018-02-01

This paper proposes an optimized lighting method of applying a shaped-function signal for increasing the dynamic range of light emitting diode (LED)-multispectral imaging system. The optimized lighting method is based on the linear response zone of the analog-to-digital conversion (ADC) and the spectral response of the camera. The auxiliary light at a higher sensitivity-camera area is introduced to increase the A/D quantization levels that are within the linear response zone of ADC and improve the signal-to-noise ratio. The active light is modulated by the shaped-function signal to improve the gray-scale resolution of the image. And the auxiliary light is modulated by the constant intensity signal, which is easy to acquire the images under the active light irradiation. The least square method is employed to precisely extract the desired images. One wavelength in multispectral imaging based on LED illumination was taken as an example. It has been proven by experiments that the gray-scale resolution and the accuracy of information of the images acquired by the proposed method were both significantly improved. The optimum method opens up avenues for the hyperspectral imaging of biological tissue.

Microprocessor-based multichannel flutter monitor using dynamic strain gage signals

NASA Technical Reports Server (NTRS)

Smalley, R. R.

1976-01-01

Two microprocessor-based multichannel monitors for monitoring strain gage signals during aerodynamic instability (flutter) testing in production type turbojet engines were described. One system monitors strain gage signals in the time domain and gives an output indication whenever the signal amplitude of any gage exceeds a pre-set alarm or abort level for that particular gage. The second system monitors the strain gage signals in the frequency domain and therefore is able to use both the amplitude and frequency information. Thus, an alarm signal is given whenever the spectral content of the strain gage signal exceeds, at any point, its corresponding amplitude vs. frequency limit profiles. Each system design is described with details on design trade-offs, hardware, software, and operating experience.

Dimensional analysis of acoustically propagated signals

NASA Technical Reports Server (NTRS)

Hansen, Scott D.; Thomson, Dennis W.

1993-01-01

Traditionally, long term measurements of atmospherically propagated sound signals have consisted of time series of multiminute averages. Only recently have continuous measurements with temporal resolution corresponding to turbulent time scales been available. With modern digital data acquisition systems we now have the capability to simultaneously record both acoustical and meteorological parameters with sufficient temporal resolution to allow us to examine in detail relationships between fluctuating sound and the meteorological variables, particularly wind and temperature, which locally determine the acoustic refractive index. The atmospheric acoustic propagation medium can be treated as a nonlinear dynamical system, a kind of signal processor whose innards depend on thermodynamic and turbulent processes in the atmosphere. The atmosphere is an inherently nonlinear dynamical system. In fact one simple model of atmospheric convection, the Lorenz system, may well be the most widely studied of all dynamical systems. In this paper we report some results of our having applied methods used to characterize nonlinear dynamical systems to study the characteristics of acoustical signals propagated through the atmosphere. For example, we investigate whether or not it is possible to parameterize signal fluctuations in terms of fractal dimensions. For time series one such parameter is the limit capacity dimension. Nicolis and Nicolis were among the first to use the kind of methods we have to study the properties of low dimension global attractors.

Seismic Signals reveal Precursors, Force History and Runout Dynamics of the Tsunami-creating Askja Caldera Landslide, July 21, 2014

NASA Astrophysics Data System (ADS)

Schöpa, A.; Chao, W. A.; Burtin, A.; Hovius, N.

2016-12-01

We have analysed signals from a network of 52 seismic stations that recorded a large landslide at the steep-sided Askja caldera, Central Iceland, on 21 July 2014. As no direct observations where made, the seismic signals are a very valuable record not only to describe the landslide dynamics in great detail but also to identify triggers and precursors of the slide useful for early warning purposes. This study is motivated by the high hazard potential of the side as the landslide created a tsunami in the caldera lake with waves up to 60 m high reaching famous tourist spots at the northern lake shore. Analysis of the high frequencies reveals that the main slope failure started at 23.24UTC. The relatively long rise time of 40 s until the maximum peak ground velocity was reached points towards cascading failure of the caldera wall. The high seismic energies recorded during the first two minutes of the slide are the result of colliding and impacting blocks. Velocity peaks in the seismic signals following the main failure are indicative for subsequent slope failures that occur less frequent, with shorter duration and lower amplitude during the twelve hours after the main event. The high frequency records of the stations up to 30 km away from the landslide source area show that the background noise level started to increase 20 min before the main failure, with amplitudes up to three times the background level about seven minutes before the main slide. Five minutes before the main failure, amplitudes decreased back to the background level. The characteristic increase and decrease in ground velocities before the main landslide could be implemented in a monitoring and early warning system of the caldera walls at Askjas. Inversion of the long-period signals (0.025-0.05 Hz) enables us to describe the history of the forces acting on the Earth during the landslide. The maximum acceleration of the moving mass was reached 40 s after the start of the slide with unloading forces

Effects of the epilarynx area on vocal fold dynamics and the primary voice signal.

PubMed

Döllinger, Michael; Berry, David A; Luegmair, Georg; Hüttner, Björn; Bohr, Christopher

2012-05-01

For the analysis of vocal fold dynamics, sub- and supraglottal influences must be taken into account, as recent studies have shown. In this work, we analyze the influence of changes in the epilaryngeal area on vocal fold dynamics. We investigate two excised female larynges in a hemilarynx setup combined with a synthetic vocal tract consisting of hard plastic and simulating the vowel /a/. Eigenmodes, amplitudes, and velocities of the oscillations, the subglottal pressures (P(sub)), and sound pressure levels (SPLs) of the generated signal are investigated as a function of three distinctive epilaryngeal areas (28.4 mm(2), 71.0 mm(2), and 205.9 mm(2)). The results showed that the SPL is independent of the epilarynx cross section and exhibits a nonlinear relation to the insufflated airflow. The P(sub) decreased with an increase in the epilaryngeal area and displayed linear relations to the airflow. The principal eigenfunctions (EEFs) from the vocal fold dynamics exhibited lateral movement for the first EEF and rotational motion for the second EEF. In total, the first two EEFs covered a minimum of 60% of the energy, with an average of more than 50% for the first EEF. Correlations to the epilarynx areas were not found. Maximal values for amplitudes (up to 2.5 mm) and velocities (up to 1.57 mm/ms) changed with varying epilaryngeal area but did not show consistent behavior for both larynges. We conclude that the size of the epilaryngeal area has significant influence on vocal fold dynamics but does not significantly affect the resultant SPL. Copyright © 2012 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

Comparative genomic analyses reveal a vast, novel network of nucleotide-centric systems in biological conflicts, immunity and signaling

PubMed Central

Burroughs, A. Maxwell; Zhang, Dapeng; Schäffer, Daniel E.; Iyer, Lakshminarayan M.; Aravind, L.

2015-01-01

Cyclic di- and linear oligo-nucleotide signals activate defenses against invasive nucleic acids in animal immunity; however, their evolutionary antecedents are poorly understood. Using comparative genomics, sequence and structure analysis, we uncovered a vast network of systems defined by conserved prokaryotic gene-neighborhoods, which encode enzymes generating such nucleotides or alternatively processing them to yield potential signaling molecules. The nucleotide-generating enzymes include several clades of the DNA-polymerase β-like superfamily (including Vibrio cholerae DncV), a minimal version of the CRISPR polymerase and DisA-like cyclic-di-AMP synthetases. Nucleotide-binding/processing domains include TIR domains and members of a superfamily prototyped by Smf/DprA proteins and base (cytokinin)-releasing LOG enzymes. They are combined in conserved gene-neighborhoods with genes for a plethora of protein superfamilies, which we predict to function as nucleotide-sensors and effectors targeting nucleic acids, proteins or membranes (pore-forming agents). These systems are sometimes combined with other biological conflict-systems such as restriction-modification and CRISPR/Cas. Interestingly, several are coupled in mutually exclusive neighborhoods with either a prokaryotic ubiquitin-system or a HORMA domain-PCH2-like AAA+ ATPase dyad. The latter are potential precursors of equivalent proteins in eukaryotic chromosome dynamics. Further, components from these nucleotide-centric systems have been utilized in several other systems including a novel diversity-generating system with a reverse transcriptase. We also found the Smf/DprA/LOG domain from these systems to be recruited as a predicted nucleotide-binding domain in eukaryotic TRPM channels. These findings point to evolutionary and mechanistic links, which bring together CRISPR/Cas, animal interferon-induced immunity, and several other systems that combine nucleic-acid-sensing and nucleotide-dependent signaling

Interpretation of interference signals in label free integrated interferometric biosensors

NASA Astrophysics Data System (ADS)

Heikkinen, Hanna; Wang, Meng; Okkonen, Matti; Hast, Jukka; Myllylä, Risto

2006-02-01

In the future fast, simple and reliable biosensors will be needed to detect various analytes from different biosamples. This is due to fact that the needs of traditional health care are changing. In the future homecare of patients and peoples' responsibility for their own health will increase. Also, different wellness applications need new parameters to be analysed, reducing costs of traditional health care, which are increasing rapidly. One fascinating and promising sensor type for these applications is an integrated optical interferometric immunosensor, which is manufactured using organic materials. The use of organic materials opens up enormous possibilities to develop different biochemical functions. In label free biosensors the measurement is based on detecting changes in refractive index, which typically are in the range of 10 -6-10 -8 [1]. In this research, theoretically generated interferograms are used to compare various signal processing methods. The goal is to develop an efficient method to analyse the interferogram. Different time domain signal processing methods are studied to determine the measuring resolution and efficiency of these methods. A low cost CCD -element is used in detecting the interferogram dynamics. It was found that in most of the signal processing methods the measuring resolution was mainly limited by pixel size. With calculation of Pearson's correlation coefficient, subpixel resolution was achieved which means that nanometer range optical path differences can be measured. This results in the refractive index resolution of the order of 10 -7.

Chaotic system detection of weak seismic signals

NASA Astrophysics Data System (ADS)

Li, Y.; Yang, B. J.; Badal, J.; Zhao, X. P.; Lin, H. B.; Li, R. L.

2009-09-01

When the signal-to-noise (S/N) ratio is less than -3 dB or even 0 dB, seismic events are generally difficult to identify from a common shot record. To overcome this type of problem we present a method to detect weak seismic signals based on the oscillations described by a chaotic dynamic system in phase space. The basic idea is that a non-linear chaotic oscillator is strongly immune to noise. Such a dynamic system is less influenced by noise, but it is more sensitive to periodic signals, changing from a chaotic state to a large-scale periodic phase state when excited by a weak signal. With the purpose of checking the possible contamination of the signal by noise, we have performed a numerical experiment with an oscillator controlled by the Duffing-Holmes equation, taking a distorted Ricker wavelet sequence as input signal. In doing so, we prove that the oscillator system is able to reach a large-scale periodic phase state in a strong noise environment. In the case of a common shot record with low S/N ratio, the onsets reflected from a same interface are similar to one other and can be put on a single trace with a common reference time and the periodicity of the so-generated signal follows as a consequence of moveout at a particular scanning velocity. This operation, which is called `horizontal dynamic correction' and leads to a nearly periodic signal, is implemented on synthetic wavelet sequences taking various sampling arrival times and scanning velocities. Thereafter, two tests, both in a noisy ambient of -3.7 dB, are done using a chaotic oscillator: the first demonstrates the capability of the method to really detect a weak seismic signal; the second takes care of the fundamental weakness of the dynamic correction coming from the use of a particular scanning velocity, which is investigated from the effect caused by near-surface lateral velocity variation on the periodicity of the reconstructed seismic signal. Finally, we have developed an application of the

Flagellar dynamics reveal the distribution of chemotactic signaling molecule CheY-P in E. coli

NASA Astrophysics Data System (ADS)

Bano, Roshni; Mears, Patrick; Chemla, Yann; Golding, Ido

E. colicells swim in a random walk consisting of ''runs'' - during which the flagella that propel the cell rotate counter-clockwise (CCW) - and ''tumbles''- during which one or more flagella rotate clockwise (CW). The tumbling frequency is modulated by the phosphorylation state of the signaling molecule CheY, which depends on the cell's environment. Phosphorylated CheY (CheY-P) binds to a flagellar motor and engenders a change in rotation state from CCW to CW. Despite advances in methods used to observe chemotactic signaling, it remains a challenge to measure the CheY-P level in cells directly. Here, we used an optical trap assay coupled with fluorescence microscopy to observe the dynamics of fluorescently labelled flagella in individual cells. By measuring the distribution of flagellar states in multi-flagellated cells and using our recent finding that each flagellar motor independently measures the cellular CheY-P concentration, we are able to extract the probability distribution of the CheY-P level in the cell. This analysis reveals the magnitude of fluctuations in chemotactic signaling in the live cell. We further investigate how this CheY-P distribution changes when cells encounter chemical gradients and perform chemotaxis. This work was supported by the National Science Foundation (NSF) through the Centre for Physics of Living Cells (CPLC).

Interplay between Functional Connectivity and Scale-Free Dynamics in Intrinsic fMRI Networks

PubMed Central

Ciuciu, Philippe; Abry, Patrice; He, Biyu J.

2014-01-01

Studies employing functional connectivity-type analyses have established that spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signals are organized within large-scale brain networks. Meanwhile, fMRI signals have been shown to exhibit 1/f-type power spectra – a hallmark of scale-free dynamics. We studied the interplay between functional connectivity and scale-free dynamics in fMRI signals, utilizing the fractal connectivity framework – a multivariate extension of the univariate fractional Gaussian noise model, which relies on a wavelet formulation for robust parameter estimation. We applied this framework to fMRI data acquired from healthy young adults at rest and performing a visual detection task. First, we found that scale-invariance existed beyond univariate dynamics, being present also in bivariate cross-temporal dynamics. Second, we observed that frequencies within the scale-free range do not contribute evenly to inter-regional connectivity, with a systematically stronger contribution of the lowest frequencies, both at rest and during task. Third, in addition to a decrease of the Hurst exponent and inter-regional correlations, task performance modified cross-temporal dynamics, inducing a larger contribution of the highest frequencies within the scale-free range to global correlation. Lastly, we found that across individuals, a weaker task modulation of the frequency contribution to inter-regional connectivity was associated with better task performance manifesting as shorter and less variable reaction times. These findings bring together two related fields that have hitherto been studied separately – resting-state networks and scale-free dynamics, and show that scale-free dynamics of human brain activity manifest in cross-regional interactions as well. PMID:24675649

Dynamics of BMP signaling in limb bud mesenchyme and polydactyly.

PubMed

Norrie, Jacqueline L; Lewandowski, Jordan P; Bouldin, Cortney M; Amarnath, Smita; Li, Qiang; Vokes, Martha S; Ehrlich, Lauren I R; Harfe, Brian D; Vokes, Steven A

2014-09-15

Mutations in the Bone Morphogenetic Protein (BMP) pathway are associated with a range of defects in skeletal formation. Genetic analysis of BMP signaling requirements is complicated by the presence of three partially redundant BMPs that are required for multiple stages of limb development. We generated an inducible allele of a BMP inhibitor, Gremlin, which reduces BMP signaling. We show that BMPs act in a dose and time dependent manner in which early reduction of BMPs result in digit loss, while inhibiting overall BMP signaling between E10.5 and E11.5 allows polydactylous digit formation. During this period, inhibiting BMPs extends the duration of FGF signaling. Sox9 is initially expressed in normal digit ray domains but at reduced levels that correlate with the reduction in BMP signaling. The persistence of elevated FGF signaling likely promotes cell proliferation and survival, inhibiting the activation of Sox9 and secondarily, inhibiting the differentiation of Sox9-expressing chondrocytes. Our results provide new insights into the timing and clarify the mechanisms underlying BMP signaling during digit morphogenesis. Copyright © 2014 Elsevier Inc. All rights reserved.

Deciphering complex dynamics of water counteraction around secondary structural elements of allosteric protein complex: Case study of SAP-SLAM system in signal transduction cascade

NASA Astrophysics Data System (ADS)

Samanta, Sudipta; Mukherjee, Sanchita

2018-01-01

The first hydration shell of a protein exhibits heterogeneous behavior owing to several attributes, majorly local polarity and structural flexibility as revealed by solvation dynamics of secondary structural elements. We attempt to recognize the change in complex water counteraction generated due to substantial alteration in flexibility during protein complex formation. The investigation is carried out with the signaling lymphocytic activation molecule (SLAM) family of receptors, expressed by an array of immune cells, and interacting with SLAM-associated protein (SAP), composed of one SH2 domain. All atom molecular dynamics simulations are employed to the aqueous solutions of free SAP and SLAM-peptide bound SAP. We observed that water dynamics around different secondary structural elements became highly affected as well as nicely correlated with the SLAM-peptide induced change in structural rigidity obtained by thermodynamic quantification. A few instances of contradictory dynamic features of water to the change in structural flexibility are explained by means of occluded polar residues by the peptide. For βD, EFloop, and BGloop, both structural flexibility and solvent accessibility of the residues confirm the obvious contribution. Most importantly, we have quantified enhanced restriction in water dynamics around the second Fyn-binding site of the SAP due to SAP-SLAM complexation, even prior to the presence of Fyn. This observation leads to a novel argument that SLAM induced more restricted water molecules could offer more water entropic contribution during the subsequent Fyn binding and provide enhanced stability to the SAP-Fyn complex in the signaling cascade. Finally, SLAM induced water counteraction around the second binding site of the SAP sheds light on the allosteric property of the SAP, which becomes an integral part of the underlying signal transduction mechanism.

Deciphering complex dynamics of water counteraction around secondary structural elements of allosteric protein complex: Case study of SAP-SLAM system in signal transduction cascade.

PubMed

Samanta, Sudipta; Mukherjee, Sanchita

2018-01-28

The first hydration shell of a protein exhibits heterogeneous behavior owing to several attributes, majorly local polarity and structural flexibility as revealed by solvation dynamics of secondary structural elements. We attempt to recognize the change in complex water counteraction generated due to substantial alteration in flexibility during protein complex formation. The investigation is carried out with the signaling lymphocytic activation molecule (SLAM) family of receptors, expressed by an array of immune cells, and interacting with SLAM-associated protein (SAP), composed of one SH2 domain. All atom molecular dynamics simulations are employed to the aqueous solutions of free SAP and SLAM-peptide bound SAP. We observed that water dynamics around different secondary structural elements became highly affected as well as nicely correlated with the SLAM-peptide induced change in structural rigidity obtained by thermodynamic quantification. A few instances of contradictory dynamic features of water to the change in structural flexibility are explained by means of occluded polar residues by the peptide. For βD, EFloop, and BGloop, both structural flexibility and solvent accessibility of the residues confirm the obvious contribution. Most importantly, we have quantified enhanced restriction in water dynamics around the second Fyn-binding site of the SAP due to SAP-SLAM complexation, even prior to the presence of Fyn. This observation leads to a novel argument that SLAM induced more restricted water molecules could offer more water entropic contribution during the subsequent Fyn binding and provide enhanced stability to the SAP-Fyn complex in the signaling cascade. Finally, SLAM induced water counteraction around the second binding site of the SAP sheds light on the allosteric property of the SAP, which becomes an integral part of the underlying signal transduction mechanism.

Design and use of multisine signals for Li-ion battery equivalent circuit modelling. Part 1: Signal design

NASA Astrophysics Data System (ADS)

Widanage, W. D.; Barai, A.; Chouchelamane, G. H.; Uddin, K.; McGordon, A.; Marco, J.; Jennings, P.

2016-08-01

The Pulse Power Current (PPC) profile is often the signal of choice for obtaining the parameters of a Lithium-ion (Li-ion) battery Equivalent Circuit Model (ECM). Subsequently, a drive-cycle current profile is used as a validation signal. Such a profile, in contrast to a PPC, is more dynamic in both the amplitude and frequency bandwidth. Modelling errors can occur when using PPC data for parametrisation since the model is optimised over a narrower bandwidth than the validation profile. A signal more representative of a drive-cycle, while maintaining a degree of generality, is needed to reduce such modelling errors. In Part 1 of this 2-part paper a signal design technique defined as a pulse-multisine is presented. This superimposes a signal known as a multisine to a discharge, rest and charge base signal to achieve a profile more dynamic in amplitude and frequency bandwidth, and thus more similar to a drive-cycle. The signal improves modelling accuracy and reduces the experimentation time, per state-of-charge (SoC) and temperature, to several minutes compared to several hours for an PPC experiment.

Infrasonic cardiac signals: complementary windows to cardiovascular dynamics.

PubMed

Tavakolian, Kouhyar; Ngai, Brandon; Blaber, Andrew P; Kaminska, Bozena

2011-01-01

New approaches to fairly old noninvasive cardiology tools, based on studying low frequency vibrations created by the heart on the body, were reviewed. These signals were divided and studied in two categories and compared in their capability for estimation of hemodynamic parameters. In particular one representative signal of each category, seismocardiogram and ultra-low frequency ballistocardiogram, were selected and compared to each other in their correspondence to physiological events behind their waves.

Complex Dynamics of Equatorial Scintillation

NASA Astrophysics Data System (ADS)

Piersanti, Mirko; Materassi, Massimo; Forte, Biagio; Cicone, Antonio

2017-04-01

Radio power scintillation, namely highly irregular fluctuations of the power of trans-ionospheric GNSS signals, is the effect of ionospheric plasma turbulence. The scintillation patterns on radio signals crossing the medium inherit the ionospheric turbulence characteristics of inter-scale coupling, local randomness and large time variability. On this basis, the remote sensing of local features of the turbulent plasma is feasible by studying radio scintillation induced by the ionosphere. The distinctive character of intermittent turbulent media depends on the fluctuations on the space- and time-scale statistical properties of the medium. Hence, assessing how the signal fluctuation properties vary under different Helio-Geophysical conditions will help to understand the corresponding dynamics of the turbulent medium crossed by the signal. Data analysis tools, provided by complex system science, appear to be best fitting to study the response of a turbulent medium, as the Earth's equatorial ionosphere, to the non-linear forcing exerted by the Solar Wind (SW). In particular we used the Adaptive Local Iterative Filtering, the Wavelet analysis and the Information theory data analysis tool. We have analysed the radio scintillation and ionospheric fluctuation data at low latitude focusing on the time and space multi-scale variability and on the causal relationship between forcing factors from the SW environment and the ionospheric response.

Functional dynamics of cell surface membrane proteins.

PubMed

Nishida, Noritaka; Osawa, Masanori; Takeuchi, Koh; Imai, Shunsuke; Stampoulis, Pavlos; Kofuku, Yutaka; Ueda, Takumi; Shimada, Ichio

2014-04-01

Cell surface receptors are integral membrane proteins that receive external stimuli, and transmit signals across plasma membranes. In the conventional view of receptor activation, ligand binding to the extracellular side of the receptor induces conformational changes, which convert the structure of the receptor into an active conformation. However, recent NMR studies of cell surface membrane proteins have revealed that their structures are more dynamic than previously envisioned, and they fluctuate between multiple conformations in an equilibrium on various timescales. In addition, NMR analyses, along with biochemical and cell biological experiments indicated that such dynamical properties are critical for the proper functions of the receptors. In this review, we will describe several NMR studies that revealed direct linkage between the structural dynamics and the functions of the cell surface membrane proteins, such as G-protein coupled receptors (GPCRs), ion channels, membrane transporters, and cell adhesion molecules. Copyright © 2013 Elsevier Inc. All rights reserved.

Inhibition of glycogen phosphorylation induces changes in cellular proteome and signaling pathways in MIA pancreatic cancer cells

PubMed Central

Ma, Danjun; Wang, Jiarui; Zhao, Yingchun; Lee, Wai-Nang Paul; Xiao, Jing; Go, Vay Liang W.; Wang, Qi; Recker, Robert; Xiao, Gary Guishan

2011-01-01

Objectives Novel quantitative proteomic approaches were used to study the effects of inhibition of glycogen phosphorylase on proteome and signaling pathways in MIA PaCa-2 pancreatic cancer cells. Methods We performed quantitative proteomic analysis in MIA PaCa-2 cancer cells treated with a stratified dose of CP-320626 (25 μM, 50 μM and 100 μM). The effect of metabolic inhibition on cellular protein turnover dynamics was also studied using the modified SILAC method (mSILAC). Results A total of twenty-two protein spots and four phosphoprotein spots were quantitatively analyzed. We found that dynamic expression of total proteins and phosphoproteins was significantly changed in MIA PaCa-2 cells treated with an incremental dose of CP-320626. Functional analyses suggested that most of the proteins differentially expressed were in the pathways of MAPK/ERK and TNF-α/NF-κB. Conclusions Signaling pathways and metabolic pathways share many common cofactors and substrates forming an extended metabolic network. The restriction of substrate through one pathway such as inhibition of glycogen phosphorylation induces pervasive metabolomic and proteomic changes manifested in protein synthesis, breakdown and post-translational modification of signaling molecules. Our results suggest that quantitative proteomic is an important approach to understand the interaction between metabolism and signaling pathways. PMID:22158071

Extraction of the respiratory signal from small-animal CT projections for a retrospective gating method

NASA Astrophysics Data System (ADS)

Chavarrías, C.; Vaquero, J. J.; Sisniega, A.; Rodríguez-Ruano, A.; Soto-Montenegro, M. L.; García-Barreno, P.; Desco, M.

2008-09-01

We propose a retrospective respiratory gating algorithm to generate dynamic CT studies. To this end, we compared three different methods of extracting the respiratory signal from the projections of small-animal cone-beam computed tomography (CBCT) scanners. Given a set of frames acquired from a certain axial angle, subtraction of their average image from each individual frame produces a set of difference images. Pixels in these images have positive or negative values (according to the respiratory phase) in those areas where there is lung movement. The respiratory signals were extracted by analysing the shape of the histogram of these difference images: we calculated the first four central and non-central moments. However, only odd-order moments produced the desired breathing signal, as the even-order moments lacked information about the phase. Each of these curves was compared to a reference signal recorded by means of a pneumatic pillow. Given the similar correlation coefficients yielded by all of them, we selected the mean to implement our retrospective protocol. Respiratory phase bins were separated, reconstructed independently and included in a dynamic sequence, suitable for cine playback. We validated our method in five adult rat studies by comparing profiles drawn across the diaphragm dome, with and without retrospective respiratory gating. Results showed a sharper transition in the gated reconstruction, with an average slope improvement of 60.7%.

HIV-1 Nef limits communication between linker of activated T cells and SLP-76 to reduce formation of SLP-76-signaling microclusters following TCR stimulation.

PubMed

Abraham, Libin; Bankhead, Peter; Pan, Xiaoyu; Engel, Ulrike; Fackler, Oliver T

2012-08-15

Signal initiation by engagement of the TCR triggers actin rearrangements, receptor clustering, and dynamic organization of signaling complexes to elicit and sustain downstream signaling. Nef, a pathogenicity factor of HIV, disrupts early TCR signaling in target T cells. To define the mechanism underlying this Nef-mediated signal disruption, we employed quantitative single-cell microscopy following surface-mediated TCR stimulation that allows for dynamic visualization of distinct signaling complexes as microclusters (MCs). Despite marked inhibition of actin remodeling and cell spreading, the induction of MCs containing TCR-CD3 or ZAP70 was not affected significantly by Nef. However, Nef potently inhibited the subsequent formation of MCs positive for the signaling adaptor Src homology-2 domain-containing leukocyte protein of 76 kDa (SLP-76) to reduce MC density in Nef-expressing and HIV-1-infected T cells. Further analyses suggested that Nef prevents formation of SLP-76 MCs at the level of the upstream adaptor protein, linker of activated T cells (LAT), that couples ZAP70 to SLP-76. Nef did not disrupt pre-existing MCs positive for LAT. However, the presence of the viral protein prevented de novo recruitment of active LAT into MCs due to retargeting of LAT to an intracellular compartment. These modulations in MC formation and composition depended on Nef's ability to simultaneously disrupt both actin remodeling and subcellular localization of TCR-proximal machinery. Nef thus employs a dual mechanism to disturb early TCR signaling by limiting the communication between LAT and SLP-76 and preventing the dynamic formation of SLP-76-signaling MCs.

On protection of Freedom's solar dynamic radiator from the orbital debris environment. Part 1: Preliminary analyses and testing

NASA Technical Reports Server (NTRS)

Rhatigan, Jennifer L.; Christiansen, Eric L.; Fleming, Michael L.

1990-01-01

A great deal of experimentation and analysis was performed to quantify penetration thresholds of components which will experience orbital debris impacts. Penetration was found to depend upon mission specific parameters such as orbital altitude, inclination, and orientation of the component; and upon component specific parameters such as material, density and the geometry particular to its shielding. Experimental results are highly dependent upon shield configuration and cannot be extrapolated with confidence to alternate shield configurations. Also, current experimental capabilities are limited to velocities which only approach the lower limit of predicted orbital debris velocities. Therefore, prediction of the penetrating particle size for a particular component having a complex geometry remains highly uncertain. An approach is described which was developed to assess on-orbit survivability of the solar dynamic radiator due to micrometeoroid and space debris impacts. Preliminary analyses are presented to quantify the solar dynamic radiator survivability, and include the type of particle and particle population expected to defeat the radiator bumpering (i.e., penetrate a fluid flow tube). Results of preliminary hypervelocity impact testing performed on radiator panel samples (in the 6 to 7 km/sec velocity range) are also presented. Plans for further analyses and testing are discussed. These efforts are expected to lead to a radiator design which will perform to requirements over the expected lifetime.

PARD3 dysfunction in conjunction with dynamic HIPPO signaling drives cortical enlargement with massive heterotopia.

PubMed

Liu, Wenying Angela; Chen, She; Li, Zhizhong; Lee, Choong Heon; Mirzaa, Ghayda; Dobyns, William B; Ross, M Elizabeth; Zhang, Jiangyang; Shi, Song-Hai

2018-06-01

Proper organization and orderly mitosis of radial glial progenitors (RGPs) drive the formation of a laminated mammalian cortex in the correct size. However, the molecular underpinnings of the intricate process remain largely unclear. Here we show that RGP behavior and cortical development are controlled by temporally distinct actions of partitioning-defective 3 (PARD3) in concert with dynamic HIPPO signaling. RGPs lacking PARD3 exhibit developmental stage-dependent abnormal switches in division mode, resulting in an initial overproduction of RGPs located largely outside the ventricular zone at the expense of deep-layer neurons. Ectopically localized RGPs subsequently undergo accelerated and excessive neurogenesis, leading to the formation of an enlarged cortex with massive heterotopia and increased seizure susceptibility. Simultaneous removal of HIPPO pathway effectors Yes-associated protein (YAP) and transcriptional coactivator with PDZ-binding motif (TAZ) suppresses cortical enlargement and heterotopia formation. These results define a dynamic regulatory program of mammalian cortical development and highlight a progenitor origin of megalencephaly with ribbon heterotopia and epilepsy. © 2018 Liu et al.; Published by Cold Spring Harbor Laboratory Press.

Signal propagation in cortical networks: a digital signal processing approach.

PubMed

Rodrigues, Francisco Aparecido; da Fontoura Costa, Luciano

2009-01-01

This work reports a digital signal processing approach to representing and modeling transmission and combination of signals in cortical networks. The signal dynamics is modeled in terms of diffusion, which allows the information processing undergone between any pair of nodes to be fully characterized in terms of a finite impulse response (FIR) filter. Diffusion without and with time decay are investigated. All filters underlying the cat and macaque cortical organization are found to be of low-pass nature, allowing the cortical signal processing to be summarized in terms of the respective cutoff frequencies (a high cutoff frequency meaning little alteration of signals through their intermixing). Several findings are reported and discussed, including the fact that the incorporation of temporal activity decay tends to provide more diversified cutoff frequencies. Different filtering intensity is observed for each community in those networks. In addition, the brain regions involved in object recognition tend to present the highest cutoff frequencies for both the cat and macaque networks.

Signal analysis techniques for incipient failure detection in turbomachinery

NASA Technical Reports Server (NTRS)

Coffin, T.

1985-01-01

Signal analysis techniques for the detection and classification of incipient mechanical failures in turbomachinery were developed, implemented and evaluated. Signal analysis techniques available to describe dynamic measurement characteristics are reviewed. Time domain and spectral methods are described, and statistical classification in terms of moments is discussed. Several of these waveform analysis techniques were implemented on a computer and applied to dynamic signals. A laboratory evaluation of the methods with respect to signal detection capability is described. Plans for further technique evaluation and data base development to characterize turbopump incipient failure modes from Space Shuttle main engine (SSME) hot firing measurements are outlined.

Copper signaling in the brain and beyond.

PubMed

Ackerman, Cheri M; Chang, Christopher J

2018-03-30

Transition metals have been recognized and studied primarily in the context of their essential roles as structural and metabolic cofactors for biomolecules that compose living systems. More recently, an emerging paradigm of transition-metal signaling, where dynamic changes in transitional metal pools can modulate protein function, cell fate, and organism health and disease, has broadened our view of the potential contributions of these essential nutrients in biology. Using copper as a canonical example of transition-metal signaling, we highlight key experiments where direct measurement and/or visualization of dynamic copper pools, in combination with biochemical, physiological, and behavioral studies, have deciphered sources, targets, and physiological effects of copper signals.

Advances in global sensitivity analyses of demographic-based species distribution models to address uncertainties in dynamic landscapes.

PubMed

Naujokaitis-Lewis, Ilona; Curtis, Janelle M R

2016-01-01

Developing a rigorous understanding of multiple global threats to species persistence requires the use of integrated modeling methods that capture processes which influence species distributions. Species distribution models (SDMs) coupled with population dynamics models can incorporate relationships between changing environments and demographics and are increasingly used to quantify relative extinction risks associated with climate and land-use changes. Despite their appeal, uncertainties associated with complex models can undermine their usefulness for advancing predictive ecology and informing conservation management decisions. We developed a computationally-efficient and freely available tool (GRIP 2.0) that implements and automates a global sensitivity analysis of coupled SDM-population dynamics models for comparing the relative influence of demographic parameters and habitat attributes on predicted extinction risk. Advances over previous global sensitivity analyses include the ability to vary habitat suitability across gradients, as well as habitat amount and configuration of spatially-explicit suitability maps of real and simulated landscapes. Using GRIP 2.0, we carried out a multi-model global sensitivity analysis of a coupled SDM-population dynamics model of whitebark pine (Pinus albicaulis) in Mount Rainier National Park as a case study and quantified the relative influence of input parameters and their interactions on model predictions. Our results differed from the one-at-time analyses used in the original study, and we found that the most influential parameters included the total amount of suitable habitat within the landscape, survival rates, and effects of a prevalent disease, white pine blister rust. Strong interactions between habitat amount and survival rates of older trees suggests the importance of habitat in mediating the negative influences of white pine blister rust. Our results underscore the importance of considering habitat attributes along

Advances in global sensitivity analyses of demographic-based species distribution models to address uncertainties in dynamic landscapes

PubMed Central

Curtis, Janelle M.R.

2016-01-01

Developing a rigorous understanding of multiple global threats to species persistence requires the use of integrated modeling methods that capture processes which influence species distributions. Species distribution models (SDMs) coupled with population dynamics models can incorporate relationships between changing environments and demographics and are increasingly used to quantify relative extinction risks associated with climate and land-use changes. Despite their appeal, uncertainties associated with complex models can undermine their usefulness for advancing predictive ecology and informing conservation management decisions. We developed a computationally-efficient and freely available tool (GRIP 2.0) that implements and automates a global sensitivity analysis of coupled SDM-population dynamics models for comparing the relative influence of demographic parameters and habitat attributes on predicted extinction risk. Advances over previous global sensitivity analyses include the ability to vary habitat suitability across gradients, as well as habitat amount and configuration of spatially-explicit suitability maps of real and simulated landscapes. Using GRIP 2.0, we carried out a multi-model global sensitivity analysis of a coupled SDM-population dynamics model of whitebark pine (Pinus albicaulis) in Mount Rainier National Park as a case study and quantified the relative influence of input parameters and their interactions on model predictions. Our results differed from the one-at-time analyses used in the original study, and we found that the most influential parameters included the total amount of suitable habitat within the landscape, survival rates, and effects of a prevalent disease, white pine blister rust. Strong interactions between habitat amount and survival rates of older trees suggests the importance of habitat in mediating the negative influences of white pine blister rust. Our results underscore the importance of considering habitat attributes along

Quantitative proteomics reveals a dynamic association of proteins to detergent-resistant membranes upon elicitor signaling in tobacco.

PubMed

Stanislas, Thomas; Bouyssie, David; Rossignol, Michel; Vesa, Simona; Fromentin, Jérôme; Morel, Johanne; Pichereaux, Carole; Monsarrat, Bernard; Simon-Plas, Françoise

2009-09-01

A large body of evidence from the past decade supports the existence, in membrane from animal and yeast cells, of functional microdomains playing important roles in protein sorting, signal transduction, or infection by pathogens. In plants, as previously observed for animal microdomains, detergent-resistant fractions, enriched in sphingolipids and sterols, were isolated from plasma membrane. A characterization of their proteic content revealed their enrichment in proteins involved in signaling and response to biotic and abiotic stress and cell trafficking suggesting that these domains were likely to be involved in such physiological processes. In the present study, we used (14)N/(15)N metabolic labeling to compare, using a global quantitative proteomics approach, the content of tobacco detergent-resistant membranes extracted from cells treated or not with cryptogein, an elicitor of defense reaction. To analyze the data, we developed a software allowing an automatic quantification of the proteins identified. The results obtained indicate that, although the association to detergent-resistant membranes of most proteins remained unchanged upon cryptogein treatment, five proteins had their relative abundance modified. Four proteins related to cell trafficking (four dynamins) were less abundant in the detergent-resistant membrane fraction after cryptogein treatment, whereas one signaling protein (a 14-3-3 protein) was enriched. This analysis indicates that plant microdomains could, like their animal counterpart, play a role in the early signaling process underlying the setup of defense reaction. Furthermore proteins identified as differentially associated to tobacco detergent-resistant membranes after cryptogein challenge are involved in signaling and vesicular trafficking as already observed in similar studies performed in animal cells upon biological stimuli. This suggests that the ways by which the dynamic association of proteins to microdomains could participate in

Quantitative Proteomics Reveals a Dynamic Association of Proteins to Detergent-resistant Membranes upon Elicitor Signaling in Tobacco*

PubMed Central

Stanislas, Thomas; Bouyssie, David; Rossignol, Michel; Vesa, Simona; Fromentin, Jérôme; Morel, Johanne; Pichereaux, Carole; Monsarrat, Bernard; Simon-Plas, Françoise

2009-01-01

A large body of evidence from the past decade supports the existence, in membrane from animal and yeast cells, of functional microdomains playing important roles in protein sorting, signal transduction, or infection by pathogens. In plants, as previously observed for animal microdomains, detergent-resistant fractions, enriched in sphingolipids and sterols, were isolated from plasma membrane. A characterization of their proteic content revealed their enrichment in proteins involved in signaling and response to biotic and abiotic stress and cell trafficking suggesting that these domains were likely to be involved in such physiological processes. In the present study, we used 14N/15N metabolic labeling to compare, using a global quantitative proteomics approach, the content of tobacco detergent-resistant membranes extracted from cells treated or not with cryptogein, an elicitor of defense reaction. To analyze the data, we developed a software allowing an automatic quantification of the proteins identified. The results obtained indicate that, although the association to detergent-resistant membranes of most proteins remained unchanged upon cryptogein treatment, five proteins had their relative abundance modified. Four proteins related to cell trafficking (four dynamins) were less abundant in the detergent-resistant membrane fraction after cryptogein treatment, whereas one signaling protein (a 14-3-3 protein) was enriched. This analysis indicates that plant microdomains could, like their animal counterpart, play a role in the early signaling process underlying the setup of defense reaction. Furthermore proteins identified as differentially associated to tobacco detergent-resistant membranes after cryptogein challenge are involved in signaling and vesicular trafficking as already observed in similar studies performed in animal cells upon biological stimuli. This suggests that the ways by which the dynamic association of proteins to microdomains could participate in the

Dynamic Modelling of Embeddable Piezoceramic Transducers

PubMed Central

Li, Xu; Li, Hongnan; Wang, Zhijie; Song, Gangbing

2017-01-01

Embedded Lead Zirconate Titanate (PZT) transducers have been widely used in research related to monitoring the health status of concrete structures. This paper presents a dynamic model of an embeddable PZT transducer with a waterproof layer and a protecting layer. The proposed model is verified by finite-element method (FEM). Based on the proposed model, the factors influencing the dynamic property of the embeddable PZT transducers, which include the material and thickness of the protecting layer, the material and thickness of the waterproof layer, and the thickness of the PZT, are analyzed. These analyses are further validated by a series of dynamic stress transfer experiments on embeddable PZT transducers. The results show that the excitation frequency can significantly affect the stress transfer of the PZT transducer in terms of both amplitude and signal phase. The natural frequency in the poling direction for the PZT transducer is affected by the material properties and the thickness of the waterproof and protecting layers. The studies in this paper will provide a scientific basis to design embeddable PZT transducers with special functions. PMID:29206150

Detection of signals in mRNAs that influence translation.

PubMed

Brown, Chris M; Jacobs, Grant; Stockwell, Peter; Schreiber, Mark

2003-01-01

Genome sequencing efforts mean that we now have extensive data from a wide range of organisms to study. Understanding the differing natures of the biology of these organisms is an important aim of genome analysis. We are interested in signals that affect translation of mRNAs. Some signals in the mRNA influence how efficiently it is translated into protein. Previous studies have indicated that many important signals are located around the initiation and termination codons. We have developed tools described here to extract the relevant sequence regions from GenBank. To create databases organised by species, or higher taxonomic groupings (eg planta), a program was developed to dynamically view and edit the taxonomy database. Data from relevant species were then extracted using our Genbank feature table parser. We analysed all available sequences, particularly those from complete genomes. Patterns were then identified using information theory. The software is available from http://transterm.otago.ac.nz. Patterns around the initiation codons for most of the organisms fall into two groups, containing the previously known Shine-Dalgarno and Kozaks efficiency signals. However, we have identified several organisms that appear to utilise novel systems. Our analysis indicates that some organisms with extremely high GC% genomes do not have a strong dependence on base pairing ribosome binding sites, as the complementary sequence is absent from many genes.

Resilience and Controllability of Dynamic Collective Behaviors

PubMed Central

Komareji, Mohammad; Bouffanais, Roland

2013-01-01

The network paradigm is used to gain insight into the structural root causes of the resilience of consensus in dynamic collective behaviors, and to analyze the controllability of the swarm dynamics. Here we devise the dynamic signaling network which is the information transfer channel underpinning the swarm dynamics of the directed interagent connectivity based on a topological neighborhood of interactions. The study of the connectedness of the swarm signaling network reveals the profound relationship between group size and number of interacting neighbors, which is found to be in good agreement with field observations on flock of starlings [Ballerini et al. (2008) Proc. Natl. Acad. Sci. USA, 105: 1232]. Using a dynamical model, we generate dynamic collective behaviors enabling us to uncover that the swarm signaling network is a homogeneous clustered small-world network, thus facilitating emergent outcomes if connectedness is maintained. Resilience of the emergent consensus is tested by introducing exogenous environmental noise, which ultimately stresses how deeply intertwined are the swarm dynamics in the physical and network spaces. The availability of the signaling network allows us to analytically establish for the first time the number of driver agents necessary to fully control the swarm dynamics. PMID:24358209

Nonlinear Complexity Analysis of Brain fMRI Signals in Schizophrenia

PubMed Central

Sokunbi, Moses O.; Gradin, Victoria B.; Waiter, Gordon D.; Cameron, George G.; Ahearn, Trevor S.; Murray, Alison D.; Steele, Douglas J.; Staff, Roger T.

2014-01-01

We investigated the differences in brain fMRI signal complexity in patients with schizophrenia while performing the Cyberball social exclusion task, using measures of Sample entropy and Hurst exponent (H). 13 patients meeting diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM IV) criteria for schizophrenia and 16 healthy controls underwent fMRI scanning at 1.5 T. The fMRI data of both groups of participants were pre-processed, the entropy characterized and the Hurst exponent extracted. Whole brain entropy and H maps of the groups were generated and analysed. The results after adjusting for age and sex differences together show that patients with schizophrenia exhibited higher complexity than healthy controls, at mean whole brain and regional levels. Also, both Sample entropy and Hurst exponent agree that patients with schizophrenia have more complex fMRI signals than healthy controls. These results suggest that schizophrenia is associated with more complex signal patterns when compared to healthy controls, supporting the increase in complexity hypothesis, where system complexity increases with age or disease, and also consistent with the notion that schizophrenia is characterised by a dysregulation of the nonlinear dynamics of underlying neuronal systems. PMID:24824731

Structural dynamics of the cell nucleus: basis for morphology modulation of nuclear calcium signaling and gene transcription.

PubMed

Queisser, Gillian; Wiegert, Simon; Bading, Hilmar

2011-01-01

Neuronal morphology plays an essential role in signal processing in the brain. Individual neurons can undergo use-dependent changes in their shape and connectivity, which affects how intracellular processes are regulated and how signals are transferred from one cell to another in a neuronal network. Calcium is one of the most important intracellular second messengers regulating cellular morphologies and functions. In neurons, intracellular calcium levels are controlled by ion channels in the plasma membrane such as NMDA receptors (NMDARs), voltage-gated calcium channels (VGCCs) and certain α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) as well as by calcium exchange pathways between the cytosol and internal calcium stores including the endoplasmic reticulum and mitochondria. Synaptic activity and the subsequent opening of ligand and/or voltage-gated calcium channels can initiate cytosolic calcium transients which propagate towards the cell soma and enter the nucleus via its nuclear pore complexes (NPCs) embedded in the nuclear envelope. We recently described the discovery that in hippocampal neurons the morphology of the nucleus affects the calcium dynamics within the nucleus. Here we propose that nuclear infoldings determine whether a nucleus functions as an integrator or detector of oscillating calcium signals. We outline possible ties between nuclear mophology and transcriptional activity and discuss the importance of extending the approach to whole cell calcium signal modeling in order to understand synapse-to-nucleus communication in healthy and dysfunctional neurons.

PCP Signaling between Migrating Neurons and their Planar-Polarized Neuroepithelial Environment Controls Filopodial Dynamics and Directional Migration

PubMed Central

Moens, Cecilia B.

2016-01-01

The planar cell polarity (PCP) pathway is a cell-contact mediated mechanism for transmitting polarity information between neighboring cells. PCP “core components” (Vangl, Fz, Pk, Dsh, and Celsr) are essential for a number of cell migratory events including the posterior migration of facial branchiomotor neurons (FBMNs) in the plane of the hindbrain neuroepithelium in zebrafish and mice. While the mechanism by which PCP signaling polarizes static epithelial cells is well understood, how PCP signaling controls highly dynamic processes like neuronal migration remains an important outstanding question given that PCP components have been implicated in a range of directed cell movements, particularly during vertebrate development. Here, by systematically disrupting PCP signaling in a rhombomere-restricted manner we show that PCP signaling is required both within FBMNs and the hindbrain rhombomere 4 environment at the time when they initiate their migration. Correspondingly, we demonstrate planar polarized localization of PCP core components Vangl2 and Fzd3a in the hindbrain neuroepithelium, and transient localization of Vangl2 at the tips of retracting FBMN filopodia. Using high-resolution timelapse imaging of FBMNs in genetic chimeras we uncover opposing cell-autonomous and non-cell-autonomous functions for Fzd3a and Vangl2 in regulating FBMN protrusive activity. Within FBMNs, Fzd3a is required to stabilize filopodia while Vangl2 has an antagonistic, destabilizing role. However, in the migratory environment Fzd3a acts to destabilize FBMN filopodia while Vangl2 has a stabilizing role. Together, our findings suggest a model in which PCP signaling between the planar polarized neuroepithelial environment and FBMNs directs migration by the selective stabilization of FBMN filopodia. PMID:26990447

Dynamic representation of partially occluded objects in primate prefrontal and visual cortex

PubMed Central

Choi, Hannah; Shea-Brown, Eric

2017-01-01

Successful recognition of partially occluded objects is presumed to involve dynamic interactions between brain areas responsible for vision and cognition, but neurophysiological evidence for the involvement of feedback signals is lacking. Here, we demonstrate that neurons in the ventrolateral prefrontal cortex (vlPFC) of monkeys performing a shape discrimination task respond more strongly to occluded than unoccluded stimuli. In contrast, neurons in visual area V4 respond more strongly to unoccluded stimuli. Analyses of V4 response dynamics reveal that many neurons exhibit two transient response peaks, the second of which emerges after vlPFC response onset and displays stronger selectivity for occluded shapes. We replicate these findings using a model of V4/vlPFC interactions in which occlusion-sensitive vlPFC neurons feed back to shape-selective V4 neurons, thereby enhancing V4 responses and selectivity to occluded shapes. These results reveal how signals from frontal and visual cortex could interact to facilitate object recognition under occlusion. PMID:28925354

Smad phosphoisoform signaling specificity: the right place at the right time.

PubMed

Matsuzaki, Koichi

2011-11-01

Transforming growth factor (TGF)-β antagonizes mitogenic Ras signaling during epithelial regeneration, but TGF-β and Ras act synergistically in driving tumor progression. Insights into these apparently contradictory effects have come from recent detailed analyses of the TGF-β signaling process. Here, we summarize the different modes of TGF-β/Ras signaling in normal epithelium and neoplasms and show how perturbation of TGF-β signaling by Ras may contribute to a shift from tumor-suppressive to protumorigenic TGF-β activity during tumor progression. Smad proteins, which convey signals from TGF-β receptors to the nucleus, have intermediate linker regions between conserved Mad homology (MH) 1 and MH2 domains. TGF-β Type I receptor and Ras-associated kinases differentially phosphorylate Smad2 and Smad3 to create C-terminally (C), linker (L) or dually (L/C) phosphorylated (p) isoforms. In epithelial homeostasis, TGF-β-mediated pSmad3C signaling opposes proliferative responses induced by mitogenic signals. During carcinogenesis, activation of cytoplasmic Ras-associated kinases including mitogen-activated protein kinase confers a selective advantage on benign tumors by shifting Smad3 signaling from a tumor-suppressive pSmad3C to an oncogenic pSmad3L pathway, leading to carcinoma in situ. Finally, at the edges of advanced carcinomas invading adjacent tissues, nuclear Ras-associated kinases such as cyclin-dependent kinases, together with cytoplasmic kinases, alter TGF-β signals to more invasive and proliferative pSmad2L/C and pSmad3L/C signaling. Taken together, TGF-β signaling specificity arises from spatiotemporal dynamics of Smad phosphoisoforms. Based on these findings, we have reason to hope that pharmacologic inhibition of linker phosphorylation might suppress progression to human advanced carcinomas by switching from protumorigenic to tumor-suppressive TGF-β signaling.

A lateral signalling pathway coordinates shape volatility during cell migration

PubMed Central

Zhang, Liang; Luga, Valbona; Armitage, Sarah K.; Musiol, Martin; Won, Amy; Yip, Christopher M.; Plotnikov, Sergey V.; Wrana, Jeffrey L.

2016-01-01

Cell migration is fundamental for both physiological and pathological processes. Migrating cells usually display high dynamics in morphology, which is orchestrated by an integrative array of signalling pathways. Here we identify a novel pathway, we term lateral signalling, comprised of the planar cell polarity (PCP) protein Pk1 and the RhoGAPs, Arhgap21/23. We show that the Pk1–Arhgap21/23 complex inhibits RhoA, is localized on the non-protrusive lateral membrane cortex and its disruption leads to the disorganization of the actomyosin network and altered focal adhesion dynamics. Pk1-mediated lateral signalling confines protrusive activity and is regulated by Smurf2, an E3 ubiquitin ligase in the PCP pathway. Furthermore, we demonstrate that dynamic interplay between lateral and protrusive signalling generates cyclical fluctuations in cell shape that we quantify here as shape volatility, which strongly correlates with migration speed. These studies uncover a previously unrecognized lateral signalling pathway that coordinates shape volatility during productive cell migration. PMID:27226243

Nonlinear Analyses of Elicited Modal, Raised, and Pressed Rabbit Phonation

PubMed Central

Awan, Shaheen N.; Novaleski, Carolyn K.; Rousseau, Bernard

2014-01-01

Objectives/Hypothesis The purpose of this study was to use nonlinear dynamic analysis methods such as phase space portraits and correlation dimension (D2) as well as descriptive spectrographic analyses to characterize acoustic signals produced during evoked rabbit phonation. Methods Seventeen New Zealand white breeder rabbits were used to perform the study. A Grass S-88 stimulator (SA Instrumentation, Encinitas, CA) and constant current isolation unit (Grass Telefactor, model PSIU6; West Warwick, RI) were used to provide electrical stimulation to laryngeal musculature, and transglottal airflow rate and stimulation current (mA) were manipulated to elicit modal, raised intensity, and pressed phonations. Central 1 second portions of the most stable portion of the acoustic waveform for modal, raised intensity, and pressed phonations were edited, and then analyzed via phase space portraits, Poincaré sections, and the estimation of the correlation dimension (D2). In an attempt to limit the effects of the highly variable and nonstationary characteristics of some of the signals being analyzed, D2 analysis was also performed on the most stable central 200 ms portion of the acoustic waveform. Descriptive analysis of each phonation was also conducted using sound spectrograms. Results Results showed that the complexity of phonation and the subsequent acoustic waveform is increased as transglottal airflow rate and degree of glottal adduction is manipulated in the evoked rabbit phonation model. In particular, phonatory complexity, as quantified via correlation dimension analyses and demonstrated via spectrographic characteristics, increases from “modal” (i.e., phonation elicited at just above the phonation threshold pressure) to raised intensity (phonation elicited by increasing transglottal airflow rate) to pressed (phonation elicited by increasing the stimulation current delivered to the larynx). Variations in a single dynamic dimension (airflow rate or adductory force

Early Warning Signals of Financial Crises with Multi-Scale Quantile Regressions of Log-Periodic Power Law Singularities.

PubMed

Zhang, Qun; Zhang, Qunzhi; Sornette, Didier

2016-01-01

We augment the existing literature using the Log-Periodic Power Law Singular (LPPLS) structures in the log-price dynamics to diagnose financial bubbles by providing three main innovations. First, we introduce the quantile regression to the LPPLS detection problem. This allows us to disentangle (at least partially) the genuine LPPLS signal and the a priori unknown complicated residuals. Second, we propose to combine the many quantile regressions with a multi-scale analysis, which aggregates and consolidates the obtained ensembles of scenarios. Third, we define and implement the so-called DS LPPLS Confidence™ and Trust™ indicators that enrich considerably the diagnostic of bubbles. Using a detailed study of the "S&P 500 1987" bubble and presenting analyses of 16 historical bubbles, we show that the quantile regression of LPPLS signals contributes useful early warning signals. The comparison between the constructed signals and the price development in these 16 historical bubbles demonstrates their significant predictive ability around the real critical time when the burst/rally occurs.

Dynamic analyses, FPGA implementation and engineering applications of multi-butterfly chaotic attractors generated from generalised Sprott C system

NASA Astrophysics Data System (ADS)

Lai, Qiang; Zhao, Xiao-Wen; Rajagopal, Karthikeyan; Xu, Guanghui; Akgul, Akif; Guleryuz, Emre

2018-01-01

This paper considers the generation of multi-butterfly chaotic attractors from a generalised Sprott C system with multiple non-hyperbolic equilibria. The system is constructed by introducing an additional variable whose derivative has a switching function to the Sprott C system. It is numerically found that the system creates two-, three-, four-, five-butterfly attractors and any other multi-butterfly attractors. First, the dynamic analyses of multi-butterfly chaotic attractors are presented. Secondly, the field programmable gate array implementation, electronic circuit realisation and random number generator are done with the multi-butterfly chaotic attractors.

Serotonin 2A Receptor Signaling Underlies LSD-induced Alteration of the Neural Response to Dynamic Changes in Music.

PubMed

Barrett, Frederick S; Preller, Katrin H; Herdener, Marcus; Janata, Petr; Vollenweider, Franz X

2017-09-28

Classic psychedelic drugs (serotonin 2A, or 5HT2A, receptor agonists) have notable effects on music listening. In the current report, blood oxygen level-dependent (BOLD) signal was collected during music listening in 25 healthy adults after administration of placebo, lysergic acid diethylamide (LSD), and LSD pretreated with the 5HT2A antagonist ketanserin, to investigate the role of 5HT2A receptor signaling in the neural response to the time-varying tonal structure of music. Tonality-tracking analysis of BOLD data revealed that 5HT2A receptor signaling alters the neural response to music in brain regions supporting basic and higher-level musical and auditory processing, and areas involved in memory, emotion, and self-referential processing. This suggests a critical role of 5HT2A receptor signaling in supporting the neural tracking of dynamic tonal structure in music, as well as in supporting the associated increases in emotionality, connectedness, and meaningfulness in response to music that are commonly observed after the administration of LSD and other psychedelics. Together, these findings inform the neuropsychopharmacology of music perception and cognition, meaningful music listening experiences, and altered perception of music during psychedelic experiences. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Roles of Diffusion Dynamics in Stem Cell Signaling and Three-Dimensional Tissue Development.

PubMed

McMurtrey, Richard J

2017-09-15

Recent advancements in the ability to construct three-dimensional (3D) tissues and organoids from stem cells and biomaterials have not only opened abundant new research avenues in disease modeling and regenerative medicine but also have ignited investigation into important aspects of molecular diffusion in 3D cellular architectures. This article describes fundamental mechanics of diffusion with equations for modeling these dynamic processes under a variety of scenarios in 3D cellular tissue constructs. The effects of these diffusion processes and resultant concentration gradients are described in the context of the major molecular signaling pathways in stem cells that both mediate and are influenced by gas and nutrient concentrations, including how diffusion phenomena can affect stem cell state, cell differentiation, and metabolic states of the cell. The application of these diffusion models and pathways is of vital importance for future studies of developmental processes, disease modeling, and tissue regeneration.

Complexity of EEG-signal in Time Domain - Possible Biomedical Application

NASA Astrophysics Data System (ADS)

Klonowski, Wlodzimierz; Olejarczyk, Elzbieta; Stepien, Robert

2002-07-01

Human brain is a highly complex nonlinear system. So it is not surprising that in analysis of EEG-signal, which represents overall activity of the brain, the methods of Nonlinear Dynamics (or Chaos Theory as it is commonly called) can be used. Even if the signal is not chaotic these methods are a motivating tool to explore changes in brain activity due to different functional activation states, e.g. different sleep stages, or to applied therapy, e.g. exposure to chemical agents (drugs) and physical factors (light, magnetic field). The methods supplied by Nonlinear Dynamics reveal signal characteristics that are not revealed by linear methods like FFT. Better understanding of principles that govern dynamics and complexity of EEG-signal can help to find `the signatures' of different physiological and pathological states of human brain, quantitative characteristics that may find applications in medical diagnostics.

Modeling SMAP Spacecraft Attitude Control Estimation Error Using Signal Generation Model

NASA Technical Reports Server (NTRS)

Rizvi, Farheen

2016-01-01

Two ground simulation software are used to model the SMAP spacecraft dynamics. The CAST software uses a higher fidelity model than the ADAMS software. The ADAMS software models the spacecraft plant, controller and actuator models, and assumes a perfect sensor and estimator model. In this simulation study, the spacecraft dynamics results from the ADAMS software are used as CAST software is unavailable. The main source of spacecraft dynamics error in the higher fidelity CAST software is due to the estimation error. A signal generation model is developed to capture the effect of this estimation error in the overall spacecraft dynamics. Then, this signal generation model is included in the ADAMS software spacecraft dynamics estimate such that the results are similar to CAST. This signal generation model has similar characteristics mean, variance and power spectral density as the true CAST estimation error. In this way, ADAMS software can still be used while capturing the higher fidelity spacecraft dynamics modeling from CAST software.

Acousto-optic RF signal acquisition system

NASA Astrophysics Data System (ADS)

Bloxham, Laurence H.

1990-09-01

This paper describes the architecture and performance of a prototype Acousto-Optic RF Signal Acquisition System designed to intercept, automatically identify, and track communication signals in the VHF band. The system covers 28.0 to 92.0 MHz with five manually selectable, dual conversion; 12.8 MHZ bandwidth front ends. An acousto-optic spectrum analyzer (AOSA) implemented using a tellurium dioxide (Te02) Bragg cell is used to channelize the 12.8 MHz pass band into 512 25 KHz channels. Polarization switching is used to suppress optical noise. Excellent isolation and dynamic range are achieved by using a linear array of 512 custom 40/50 micron fiber optic cables to collect the light at the focal plane of the AOSA and route the light to individual photodetectors. The photodetectors are operated in the photovoltaic mode to compress the greater than 60 dB input optical dynamic range into an easily processed electrical signal. The 512 signals are multiplexed and processed as a line in a video image by a customized digital image processing system. The image processor simultaneously analyzes the channelized signal data and produces a classical waterfall display.

Detecting recurrence domains of dynamical systems by symbolic dynamics.

PubMed

beim Graben, Peter; Hutt, Axel

2013-04-12

We propose an algorithm for the detection of recurrence domains of complex dynamical systems from time series. Our approach exploits the characteristic checkerboard texture of recurrence domains exhibited in recurrence plots. In phase space, recurrence plots yield intersecting balls around sampling points that could be merged into cells of a phase space partition. We construct this partition by a rewriting grammar applied to the symbolic dynamics of time indices. A maximum entropy principle defines the optimal size of intersecting balls. The final application to high-dimensional brain signals yields an optimal symbolic recurrence plot revealing functional components of the signal.

Signaling aggression.

PubMed

van Staaden, Moira J; Searcy, William A; Hanlon, Roger T

2011-01-01

From psychological and sociological standpoints, aggression is regarded as intentional behavior aimed at inflicting pain and manifested by hostility and attacking behaviors. In contrast, biologists define aggression as behavior associated with attack or escalation toward attack, omitting any stipulation about intentions and goals. Certain animal signals are strongly associated with escalation toward attack and have the same function as physical attack in intimidating opponents and winning contests, and ethologists therefore consider them an integral part of aggressive behavior. Aggressive signals have been molded by evolution to make them ever more effective in mediating interactions between the contestants. Early theoretical analyses of aggressive signaling suggested that signals could never be honest about fighting ability or aggressive intentions because weak individuals would exaggerate such signals whenever they were effective in influencing the behavior of opponents. More recent game theory models, however, demonstrate that given the right costs and constraints, aggressive signals are both reliable about strength and intentions and effective in influencing contest outcomes. Here, we review the role of signaling in lieu of physical violence, considering threat displays from an ethological perspective as an adaptive outcome of evolutionary selection pressures. Fighting prowess is conveyed by performance signals whose production is constrained by physical ability and thus limited to just some individuals, whereas aggressive intent is encoded in strategic signals that all signalers are able to produce. We illustrate recent advances in the study of aggressive signaling with case studies of charismatic taxa that employ a range of sensory modalities, viz. visual and chemical signaling in cephalopod behavior, and indicators of aggressive intent in the territorial calls of songbirds. Copyright © 2011 Elsevier Inc. All rights reserved.

Modeling of Receptor Tyrosine Kinase Signaling: Computational and Experimental Protocols.

PubMed

Fey, Dirk; Aksamitiene, Edita; Kiyatkin, Anatoly; Kholodenko, Boris N

2017-01-01

The advent of systems biology has convincingly demonstrated that the integration of experiments and dynamic modelling is a powerful approach to understand the cellular network biology. Here we present experimental and computational protocols that are necessary for applying this integrative approach to the quantitative studies of receptor tyrosine kinase (RTK) signaling networks. Signaling by RTKs controls multiple cellular processes, including the regulation of cell survival, motility, proliferation, differentiation, glucose metabolism, and apoptosis. We describe methods of model building and training on experimentally obtained quantitative datasets, as well as experimental methods of obtaining quantitative dose-response and temporal dependencies of protein phosphorylation and activities. The presented methods make possible (1) both the fine-grained modeling of complex signaling dynamics and identification of salient, course-grained network structures (such as feedback loops) that bring about intricate dynamics, and (2) experimental validation of dynamic models.

Marginal Utility of Conditional Sensitivity Analyses for Dynamic Models

EPA Science Inventory

Background/Question/MethodsDynamic ecological processes may be influenced by many factors. Simulation models thatmimic these processes often have complex implementations with many parameters. Sensitivityanalyses are subsequently used to identify critical parameters whose uncertai...

Mid-frequency Band Dynamics of Large Space Structures

NASA Technical Reports Server (NTRS)

Coppolino, Robert N.; Adams, Douglas S.

2004-01-01

High and low intensity dynamic environments experienced by a spacecraft during launch and on-orbit operations, respectively, induce structural loads and motions, which are difficult to reliably predict. Structural dynamics in low- and mid-frequency bands are sensitive to component interface uncertainty and non-linearity as evidenced in laboratory testing and flight operations. Analytical tools for prediction of linear system response are not necessarily adequate for reliable prediction of mid-frequency band dynamics and analysis of measured laboratory and flight data. A new MATLAB toolbox, designed to address the key challenges of mid-frequency band dynamics, is introduced in this paper. Finite-element models of major subassemblies are defined following rational frequency-wavelength guidelines. For computational efficiency, these subassemblies are described as linear, component mode models. The complete structural system model is composed of component mode subassemblies and linear or non-linear joint descriptions. Computation and display of structural dynamic responses are accomplished employing well-established, stable numerical methods, modern signal processing procedures and descriptive graphical tools. Parametric sensitivity and Monte-Carlo based system identification tools are used to reconcile models with experimental data and investigate the effects of uncertainties. Models and dynamic responses are exported for employment in applications, such as detailed structural integrity and mechanical-optical-control performance analyses.

Effects of controlled element dynamics on human feedforward behavior in ramp-tracking tasks.

PubMed

Laurense, Vincent A; Pool, Daan M; Damveld, Herman J; van Paassen, Marinus René M; Mulder, Max

2015-02-01

In real-life manual control tasks, human controllers are often required to follow a visible and predictable reference signal, enabling them to use feedforward control actions in conjunction with feedback actions that compensate for errors. Little is known about human control behavior in these situations. This paper investigates how humans adapt their feedforward control dynamics to the controlled element dynamics in a combined ramp-tracking and disturbance-rejection task. A human-in-the-loop experiment is performed with a pursuit display and vehicle-like controlled elements, ranging from a single integrator through second-order systems with a break frequency at either 3, 2, or 1 rad/s, to a double integrator. Because the potential benefits of feedforward control increase with steeper ramp segments in the target signal, three steepness levels are tested to investigate their possible effect on feedforward control with the various controlled elements. Analyses with four novel models of the operator, fitted to time-domain data, reveal feedforward control for all tested controlled elements and both (nonzero) tested levels of ramp steepness. For the range of controlled element dynamics investigated, it is found that humans adapt to these dynamics in their feedforward response, with a close to perfect inversion of the controlled element dynamics. No significant effects of ramp steepness on the feedforward model parameters are found.

Algorithm for removing scalp signals from functional near-infrared spectroscopy signals in real time using multidistance optodes.

PubMed

Kiguchi, Masashi; Funane, Tsukasa

2014-11-01

A real-time algorithm for removing scalp-blood signals from functional near-infrared spectroscopy signals is proposed. Scalp and deep signals have different dependencies on the source-detector distance. These signals were separated using this characteristic. The algorithm was validated through an experiment using a dynamic phantom in which shallow and deep absorptions were independently changed. The algorithm for measurement of oxygenated and deoxygenated hemoglobins using two wavelengths was explicitly obtained. This algorithm is potentially useful for real-time systems, e.g., brain-computer interfaces and neuro-feedback systems.

Using System Dynamic Model and Neural Network Model to Analyse Water Scarcity in Sudan

NASA Astrophysics Data System (ADS)

Li, Y.; Tang, C.; Xu, L.; Ye, S.

2017-07-01

Many parts of the world are facing the problem of Water Scarcity. Analysing Water Scarcity quantitatively is an important step to solve the problem. Water scarcity in a region is gauged by WSI (water scarcity index), which incorporate water supply and water demand. To get the WSI, Neural Network Model and SDM (System Dynamic Model) that depict how environmental and social factors affect water supply and demand are developed to depict how environmental and social factors affect water supply and demand. The uneven distribution of water resource and water demand across a region leads to an uneven distribution of WSI within this region. To predict WSI for the future, logistic model, Grey Prediction, and statistics are applied in predicting variables. Sudan suffers from severe water scarcity problem with WSI of 1 in 2014, water resource unevenly distributed. According to the result of modified model, after the intervention, Sudan’s water situation will become better.

Fossil-based comparative analyses reveal ancient marine ancestry erased by extinction in ray-finned fishes.

PubMed

Betancur-R, Ricardo; Ortí, Guillermo; Pyron, Robert Alexander

2015-05-01

The marine-freshwater boundary is a major biodiversity gradient and few groups have colonised both systems successfully. Fishes have transitioned between habitats repeatedly, diversifying in rivers, lakes and oceans over evolutionary time. However, their history of habitat colonisation and diversification is unclear based on available fossil and phylogenetic data. We estimate ancestral habitats and diversification and transition rates using a large-scale phylogeny of extant fish taxa and one containing a massive number of extinct species. Extant-only phylogenetic analyses indicate freshwater ancestry, but inclusion of fossils reveal strong evidence of marine ancestry in lineages now restricted to freshwaters. Diversification and colonisation dynamics vary asymmetrically between habitats, as marine lineages colonise and flourish in rivers more frequently than the reverse. Our study highlights the importance of including fossils in comparative analyses, showing that freshwaters have played a role as refuges for ancient fish lineages, a signal erased by extinction in extant-only phylogenies. © 2015 John Wiley & Sons Ltd/CNRS.

Spatiotemporal neural network dynamics for the processing of dynamic facial expressions.

PubMed

Sato, Wataru; Kochiyama, Takanori; Uono, Shota

2015-07-24

The dynamic facial expressions of emotion automatically elicit multifaceted psychological activities; however, the temporal profiles and dynamic interaction patterns of brain activities remain unknown. We investigated these issues using magnetoencephalography. Participants passively observed dynamic facial expressions of fear and happiness, or dynamic mosaics. Source-reconstruction analyses utilizing functional magnetic-resonance imaging data revealed higher activation in broad regions of the bilateral occipital and temporal cortices in response to dynamic facial expressions than in response to dynamic mosaics at 150-200 ms and some later time points. The right inferior frontal gyrus exhibited higher activity for dynamic faces versus mosaics at 300-350 ms. Dynamic causal-modeling analyses revealed that dynamic faces activated the dual visual routes and visual-motor route. Superior influences of feedforward and feedback connections were identified before and after 200 ms, respectively. These results indicate that hierarchical, bidirectional neural network dynamics within a few hundred milliseconds implement the processing of dynamic facial expressions.

Spatiotemporal neural network dynamics for the processing of dynamic facial expressions

PubMed Central

Sato, Wataru; Kochiyama, Takanori; Uono, Shota

2015-01-01

The dynamic facial expressions of emotion automatically elicit multifaceted psychological activities; however, the temporal profiles and dynamic interaction patterns of brain activities remain unknown. We investigated these issues using magnetoencephalography. Participants passively observed dynamic facial expressions of fear and happiness, or dynamic mosaics. Source-reconstruction analyses utilizing functional magnetic-resonance imaging data revealed higher activation in broad regions of the bilateral occipital and temporal cortices in response to dynamic facial expressions than in response to dynamic mosaics at 150–200 ms and some later time points. The right inferior frontal gyrus exhibited higher activity for dynamic faces versus mosaics at 300–350 ms. Dynamic causal-modeling analyses revealed that dynamic faces activated the dual visual routes and visual–motor route. Superior influences of feedforward and feedback connections were identified before and after 200 ms, respectively. These results indicate that hierarchical, bidirectional neural network dynamics within a few hundred milliseconds implement the processing of dynamic facial expressions. PMID:26206708

A Review on the Nonlinear Dynamical System Analysis of Electrocardiogram Signal.

PubMed

Nayak, Suraj K; Bit, Arindam; Dey, Anilesh; Mohapatra, Biswajit; Pal, Kunal

2018-01-01

Electrocardiogram (ECG) signal analysis has received special attention of the researchers in the recent past because of its ability to divulge crucial information about the electrophysiology of the heart and the autonomic nervous system activity in a noninvasive manner. Analysis of the ECG signals has been explored using both linear and nonlinear methods. However, the nonlinear methods of ECG signal analysis are gaining popularity because of their robustness in feature extraction and classification. The current study presents a review of the nonlinear signal analysis methods, namely, reconstructed phase space analysis, Lyapunov exponents, correlation dimension, detrended fluctuation analysis (DFA), recurrence plot, Poincaré plot, approximate entropy, and sample entropy along with their recent applications in the ECG signal analysis.

Differential Dopamine Release Dynamics in the Nucleus Accumbens Core and Shell Reveal Complementary Signals for Error Prediction and Incentive Motivation.

PubMed

Saddoris, Michael P; Cacciapaglia, Fabio; Wightman, R Mark; Carelli, Regina M

2015-08-19

Mesolimbic dopamine (DA) is phasically released during appetitive behaviors, though there is substantive disagreement about the specific purpose of these DA signals. For example, prediction error (PE) models suggest a role of learning, while incentive salience (IS) models argue that the DA signal imbues stimuli with value and thereby stimulates motivated behavior. However, within the nucleus accumbens (NAc) patterns of DA release can strikingly differ between subregions, and as such, it is possible that these patterns differentially contribute to aspects of PE and IS. To assess this, we measured DA release in subregions of the NAc during a behavioral task that spatiotemporally separated sequential goal-directed stimuli. Electrochemical methods were used to measure subsecond NAc dopamine release in the core and shell during a well learned instrumental chain schedule in which rats were trained to press one lever (seeking; SL) to gain access to a second lever (taking; TL) linked with food delivery, and again during extinction. In the core, phasic DA release was greatest following initial SL presentation, but minimal for the subsequent TL and reward events. In contrast, phasic shell DA showed robust release at all task events. Signaling decreased between the beginning and end of sessions in the shell, but not core. During extinction, peak DA release in the core showed a graded decrease for the SL and pauses in release during omitted expected rewards, whereas shell DA release decreased predominantly during the TL. These release dynamics suggest parallel DA signals capable of supporting distinct theories of appetitive behavior. Dopamine signaling in the brain is important for a variety of cognitive functions, such as learning and motivation. Typically, it is assumed that a single dopamine signal is sufficient to support these cognitive functions, though competing theories disagree on how dopamine contributes to reward-based behaviors. Here, we have found that real

Differential Dopamine Release Dynamics in the Nucleus Accumbens Core and Shell Reveal Complementary Signals for Error Prediction and Incentive Motivation

PubMed Central

Cacciapaglia, Fabio; Wightman, R. Mark; Carelli, Regina M.

2015-01-01

Mesolimbic dopamine (DA) is phasically released during appetitive behaviors, though there is substantive disagreement about the specific purpose of these DA signals. For example, prediction error (PE) models suggest a role of learning, while incentive salience (IS) models argue that the DA signal imbues stimuli with value and thereby stimulates motivated behavior. However, within the nucleus accumbens (NAc) patterns of DA release can strikingly differ between subregions, and as such, it is possible that these patterns differentially contribute to aspects of PE and IS. To assess this, we measured DA release in subregions of the NAc during a behavioral task that spatiotemporally separated sequential goal-directed stimuli. Electrochemical methods were used to measure subsecond NAc dopamine release in the core and shell during a well learned instrumental chain schedule in which rats were trained to press one lever (seeking; SL) to gain access to a second lever (taking; TL) linked with food delivery, and again during extinction. In the core, phasic DA release was greatest following initial SL presentation, but minimal for the subsequent TL and reward events. In contrast, phasic shell DA showed robust release at all task events. Signaling decreased between the beginning and end of sessions in the shell, but not core. During extinction, peak DA release in the core showed a graded decrease for the SL and pauses in release during omitted expected rewards, whereas shell DA release decreased predominantly during the TL. These release dynamics suggest parallel DA signals capable of supporting distinct theories of appetitive behavior. SIGNIFICANCE STATEMENT Dopamine signaling in the brain is important for a variety of cognitive functions, such as learning and motivation. Typically, it is assumed that a single dopamine signal is sufficient to support these cognitive functions, though competing theories disagree on how dopamine contributes to reward-based behaviors. Here, we have

Tour time in a two-route traffic system controlled by signals

NASA Astrophysics Data System (ADS)

Nagatani, Takashi; Naito, Yuichi

2011-11-01

We study the dynamic behavior of vehicular traffic in a two-route system with a series of signals (traffic lights) at low density where the number of signals on route A is different from that on route B. We investigate the dependence of the tour time on the route for some strategies of signal control. The nonlinear dynamic model of a two-route traffic system controlled by signals is presented by nonlinear maps. The vehicular traffic exhibits a very complex behavior, depending on the cycle time, the phase difference, and the irregularity. The dependence of the tour time on the route choice is clarified for the signal strategies.

Monitoring dynamic loads on wind tunnel force balances

NASA Technical Reports Server (NTRS)

Ferris, Alice T.; White, William C.

1989-01-01

Two devices have been developed at NASA Langley to monitor the dynamic loads incurred during wind-tunnel testing. The Balance Dynamic Display Unit (BDDU), displays and monitors the combined static and dynamic forces and moments in the orthogonal axes. The Balance Critical Point Analyzer scales and sums each normalized signal from the BDDU to obtain combined dynamic and static signals that represent the dynamic loads at predefined high-stress points. The display of each instrument is a multiplex of six analog signals in a way that each channel is displayed sequentially as one-sixth of the horizontal axis on a single oscilloscope trace. Thus this display format permits the operator to quickly and easily monitor the combined static and dynamic level of up to six channels at the same time.

The application of the analog signal to discrete time interval converter to the signal conditioner power supplies

NASA Technical Reports Server (NTRS)

Schoenfeld, A. D.; Yu, Y.

1973-01-01

The Analog Signal to Discrete Time Interval Converter microminiaturized module was utilized to control the signal conditioner power supplies. The multi-loop control provides outstanding static and dynamic performance characteristics, exceeding those generally associated with single-loop regulators. Eight converter boards, each containing three independent dc to dc converter, were built, tested, and delivered.

A Review on the Nonlinear Dynamical System Analysis of Electrocardiogram Signal

PubMed Central

Mohapatra, Biswajit

2018-01-01

Electrocardiogram (ECG) signal analysis has received special attention of the researchers in the recent past because of its ability to divulge crucial information about the electrophysiology of the heart and the autonomic nervous system activity in a noninvasive manner. Analysis of the ECG signals has been explored using both linear and nonlinear methods. However, the nonlinear methods of ECG signal analysis are gaining popularity because of their robustness in feature extraction and classification. The current study presents a review of the nonlinear signal analysis methods, namely, reconstructed phase space analysis, Lyapunov exponents, correlation dimension, detrended fluctuation analysis (DFA), recurrence plot, Poincaré plot, approximate entropy, and sample entropy along with their recent applications in the ECG signal analysis. PMID:29854361

Sequential pattern formation governed by signaling gradients

NASA Astrophysics Data System (ADS)

Jörg, David J.; Oates, Andrew C.; Jülicher, Frank

2016-10-01

Rhythmic and sequential segmentation of the embryonic body plan is a vital developmental patterning process in all vertebrate species. However, a theoretical framework capturing the emergence of dynamic patterns of gene expression from the interplay of cell oscillations with tissue elongation and shortening and with signaling gradients, is still missing. Here we show that a set of coupled genetic oscillators in an elongating tissue that is regulated by diffusing and advected signaling molecules can account for segmentation as a self-organized patterning process. This system can form a finite number of segments and the dynamics of segmentation and the total number of segments formed depend strongly on kinetic parameters describing tissue elongation and signaling molecules. The model accounts for existing experimental perturbations to signaling gradients, and makes testable predictions about novel perturbations. The variety of different patterns formed in our model can account for the variability of segmentation between different animal species.

Dynamic Spectral Structure Specifies Vowels for Adults and Children

PubMed Central

Nittrouer, Susan; Lowenstein, Joanna H.

2014-01-01

The dynamic specification account of vowel recognition suggests that formant movement between vowel targets and consonant margins is used by listeners to recognize vowels. This study tested that account by measuring contributions to vowel recognition of dynamic (i.e., time-varying) spectral structure and coarticulatory effects on stationary structure. Adults and children (four-and seven-year-olds) were tested with three kinds of consonant-vowel-consonant syllables: (1) unprocessed; (2) sine waves that preserved both stationary coarticulated and dynamic spectral structure; and (3) vocoded signals that primarily preserved that stationary, but not dynamic structure. Sections of two lengths were removed from syllable middles: (1) half the vocalic portion; and (2) all but the first and last three pitch periods. Adults performed accurately with unprocessed and sine-wave signals, as long as half the syllable remained; their recognition was poorer for vocoded signals, but above chance. Seven-year-olds performed more poorly than adults with both sorts of processed signals, but disproportionately worse with vocoded than sine-wave signals. Most four-year-olds were unable to recognize vowels at all with vocoded signals. Conclusions were that both dynamic and stationary coarticulated structures support vowel recognition for adults, but children attend to dynamic spectral structure more strongly because early phonological organization favors whole words. PMID:25536845

Summary of Dynamic Analyses of Selected NSS Buildings.

DTIC Science & Technology

1980-07-01

AREA & WORK UNIT NUMBERS SRI International! Menlo Park, California 94025 FEMA Work Unit 1151D 12. REPORT DATE 13. NO. OF PAGES 11. CONTROLLING OFFICE...ADDRESS (if deff. I’Om Controlling Office) , 1-,7 77 15a. DECLASSIFICATION /DOWNGRADING SCHEDULE 16. DISTRIBUTION STATEMENT (of this report) Approved for... control the final dynamic failure mechanism when there is adequate anchorage to assure full devel- * opment of the tensile membrane mode. The "/s" case

Three-Dimensional Numerical Analyses of Earth Penetration Dynamics

DTIC Science & Technology

1979-01-31

Lagrangian formulation based on the HEMP method and has been adapted and validated for treatment of normal-incidence (axisymmetric) impact and...code, is a detailed analysis of the structural response of the EPW. This analysis is generated using a nonlinear dynamic, elastic- plastic finite element...based on the HEMP scheme. Thus, the code has the same material modeling capabilities and abilities to track large scale motion found in the WAVE-L code

Singular spectrum and singular entropy used in signal processing of NC table

NASA Astrophysics Data System (ADS)

Wang, Linhong; He, Yiwen

2011-12-01

NC (numerical control) table is a complex dynamic system. The dynamic characteristics caused by backlash, friction and elastic deformation among each component are so complex that they have become the bottleneck of enhancing the positioning accuracy, tracking accuracy and dynamic behavior of NC table. This paper collects vibration acceleration signals from NC table, analyzes the signals with SVD (singular value decomposition) method, acquires the singular spectrum and calculates the singular entropy of the signals. The signal characteristics and their regulations of NC table are revealed via the characteristic quantities such as singular spectrum, singular entropy etc. The steep degrees of singular spectrums can be used to discriminate complex degrees of signals. The results show that the signals in direction of driving axes are the simplest and the signals in perpendicular direction are the most complex. The singular entropy values can be used to study the indetermination of signals. The results show that the signals of NC table are not simple signal nor white noise, the entropy values in direction of driving axe are lower, the entropy values increase along with the increment of driving speed and the entropy values at the abnormal working conditions such as resonance or creeping etc decrease obviously.

Quantifying ubiquitin signaling.

PubMed

Ordureau, Alban; Münch, Christian; Harper, J Wade

2015-05-21

Ubiquitin (UB)-driven signaling systems permeate biology, and are often integrated with other types of post-translational modifications (PTMs), including phosphorylation. Flux through such pathways is dictated by the fractional stoichiometry of distinct modifications and protein assemblies as well as the spatial organization of pathway components. Yet, we rarely understand the dynamics and stoichiometry of rate-limiting intermediates along a reaction trajectory. Here, we review how quantitative proteomic tools and enrichment strategies are being used to quantify UB-dependent signaling systems, and to integrate UB signaling with regulatory phosphorylation events, illustrated with the PINK1/PARKIN pathway. A key feature of ubiquitylation is that the identity of UB chain linkage types can control downstream processes. We also describe how proteomic and enzymological tools can be used to identify and quantify UB chain synthesis and linkage preferences. The emergence of sophisticated quantitative proteomic approaches will set a new standard for elucidating biochemical mechanisms of UB-driven signaling systems. Copyright © 2015 Elsevier Inc. All rights reserved.

Quantifying Ubiquitin Signaling

PubMed Central

Ordureau, Alban; Münch, Christian; Harper, J. Wade

2015-01-01

Ubiquitin (UB)-driven signaling systems permeate biology, and are often integrated with other types of post-translational modifications (PTMs), most notably phosphorylation. Flux through such pathways is typically dictated by the fractional stoichiometry of distinct regulatory modifications and protein assemblies as well as the spatial organization of pathway components. Yet, we rarely understand the dynamics and stoichiometry of rate-limiting intermediates along a reaction trajectory. Here, we review how quantitative proteomic tools and enrichment strategies are being used to quantify UB-dependent signaling systems, and to integrate UB signaling with regulatory phosphorylation events. A key regulatory feature of ubiquitylation is that the identity of UB chain linkage types can control downstream processes. We also describe how proteomic and enzymological tools can be used to identify and quantify UB chain synthesis and linkage preferences. The emergence of sophisticated quantitative proteomic approaches will set a new standard for elucidating biochemical mechanisms of UB-driven signaling systems. PMID:26000850

Technique for extending the range of a signal measuring circuit

DOEpatents

Chaprnka, Anthony G.; Sun, Shan C.; Vercellotti, Leonard C.

1978-01-01

An input signal supplied to a signal measuring circuit is either amplified or attenuated as necessary to establish the magnitude of the input signal within the defined dynamic range of the measuring circuit and the output signal developed by the measuring circuit is subsequently readjusted through amplification or attenuation to develop an output signal which corresponds to the magnitude of the initial input signal.

Changes in expression and secretion patterns of fibroblast growth factor 8 and Sonic Hedgehog signaling pathway molecules during murine neural stem/progenitor cell differentiation in vitro☆

PubMed Central

Lu, Jiang; Lu, Kehuan; Li, Dongsheng

2012-01-01

In the present study, we investigated the dynamic expression of fibroblast growth factor 8 and Sonic Hedgehog signaling pathway related factors in the process of in vitro hippocampal neural stem/progenitor cell differentiation from embryonic Sprague-Dawley rats or embryonic Kunming species mice, using fluorescent quantitative reverse transcription-PCR and western blot analyses. Results demonstrated that the dynamic expression of fibroblast growth factor 8 was similar to fibroblast growth factor receptor 1 expression but not to other fibroblast growth factor receptors. Enzyme-linked immunosorbent assay demonstrated that fibroblast growth factor 8 and Sonic Hedgehog signaling pathway protein factors were secreted by neural cells into the intercellular niche. Our experimental findings indicate that fibroblast growth factor 8 and Sonic Hedgehog expression may be related to the differentiation of neural stem/progenitor cells. PMID:25624789

A History of Rotorcraft Comprehensive Analyses

NASA Technical Reports Server (NTRS)

Johnson, Wayne

2013-01-01

A history of the development of rotorcraft comprehensive analyses is presented. Comprehensive analyses are digital computer programs that calculate the aeromechanical behavior of the rotor and aircraft, bringing together the most advanced models of the geometry, structure, dynamics, and aerodynamics available in rotary wing technology. The development of the major codes of the last five decades from industry, government, and universities is described. A number of common themes observed in this history are discussed.

Complexity, fractal dynamics and determinism in treadmill ambulation: Implications for clinical biomechanists.

PubMed

Hollman, John H; Watkins, Molly K; Imhoff, Angela C; Braun, Carly E; Akervik, Kristen A; Ness, Debra K

2016-08-01

Reduced inter-stride complexity during ambulation may represent a pathologic state. Evidence is emerging that treadmill training for rehabilitative purposes may constrain the locomotor system and alter gait dynamics in a way that mimics pathological states. The purpose of this study was to examine the dynamical system components of gait complexity, fractal dynamics and determinism during treadmill ambulation. Twenty healthy participants aged 23.8 (1.2) years walked at preferred walking speeds for 6min on a motorized treadmill and overground while wearing APDM 6 Opal inertial monitors. Stride times, stride lengths and peak sagittal plane trunk velocities were measured. Mean values and estimates of complexity, fractal dynamics and determinism were calculated for each parameter. Data were compared between overground and treadmill walking conditions. Mean values for each gait parameter were statistically equivalent between overground and treadmill ambulation (P>0.05). Through nonlinear analyses, however, we found that complexity in stride time signals (P<0.001), and long-range correlations in stride time and stride length signals (P=0.005 and P=0.024, respectively), were reduced on the treadmill. Treadmill ambulation induces more predictable inter-stride time dynamics and constrains fluctuations in stride times and stride lengths, which may alter feedback from destabilizing perturbations normally experienced by the locomotor control system during overground ambulation. Treadmill ambulation, therefore, may provide less opportunity for experiencing the adaptability necessary to successfully ambulate overground. Investigators and clinicians should be aware that treadmill ambulation will alter dynamic gait characteristics. Copyright © 2016 Elsevier Ltd. All rights reserved.

Synchronization transmission of laser pattern signal within uncertain switched network

NASA Astrophysics Data System (ADS)

Lü, Ling; Li, Chengren; Li, Gang; Sun, Ao; Yan, Zhe; Rong, Tingting; Gao, Yan

2017-06-01

We propose a new technology for synchronization transmission of laser pattern signal within uncertain network with controllable topology. In synchronization process, the connection of dynamic network can vary at all time according to different demands. Especially, we construct the Lyapunov function of network through designing a special semi-positive definite function, and the synchronization transmission of laser pattern signal within uncertain network with controllable topology can be realized perfectly, which effectively avoids the complicated calculation for solving the second largest eignvalue of the coupling matrix of the dynamic network in order to obtain the network synchronization condition. At the same time, the uncertain parameters in dynamic equations belonging to network nodes can also be identified accurately via designing the identification laws of uncertain parameters. In addition, there are not any limitations for the synchronization target of network in the new technology, in other words, the target can either be a state variable signal of an arbitrary node within the network or an exterior signal.

Dynamic Analyses Including Joints Of Truss Structures

NASA Technical Reports Server (NTRS)

Belvin, W. Keith

1991-01-01

Method for mathematically modeling joints to assess influences of joints on dynamic response of truss structures developed in study. Only structures with low-frequency oscillations considered; only Coulomb friction and viscous damping included in analysis. Focus of effort to obtain finite-element mathematical models of joints exhibiting load-vs.-deflection behavior similar to measured load-vs.-deflection behavior of real joints. Experiments performed to determine stiffness and damping nonlinearities typical of joint hardware. Algorithm for computing coefficients of analytical joint models based on test data developed to enable study of linear and nonlinear effects of joints on global structural response. Besides intended application to large space structures, applications in nonaerospace community include ground-based antennas and earthquake-resistant steel-framed buildings.

Next generation of network medicine: interdisciplinary signaling approaches.

PubMed

Korcsmaros, Tamas; Schneider, Maria Victoria; Superti-Furga, Giulio

2017-02-20

In the last decade, network approaches have transformed our understanding of biological systems. Network analyses and visualizations have allowed us to identify essential molecules and modules in biological systems, and improved our understanding of how changes in cellular processes can lead to complex diseases, such as cancer, infectious and neurodegenerative diseases. "Network medicine" involves unbiased large-scale network-based analyses of diverse data describing interactions between genes, diseases, phenotypes, drug targets, drug transport, drug side-effects, disease trajectories and more. In terms of drug discovery, network medicine exploits our understanding of the network connectivity and signaling system dynamics to help identify optimal, often novel, drug targets. Contrary to initial expectations, however, network approaches have not yet delivered a revolution in molecular medicine. In this review, we propose that a key reason for the limited impact, so far, of network medicine is a lack of quantitative multi-disciplinary studies involving scientists from different backgrounds. To support this argument, we present existing approaches from structural biology, 'omics' technologies (e.g., genomics, proteomics, lipidomics) and computational modeling that point towards how multi-disciplinary efforts allow for important new insights. We also highlight some breakthrough studies as examples of the potential of these approaches, and suggest ways to make greater use of the power of interdisciplinarity. This review reflects discussions held at an interdisciplinary signaling workshop which facilitated knowledge exchange from experts from several different fields, including in silico modelers, computational biologists, biochemists, geneticists, molecular and cell biologists as well as cancer biologists and pharmacologists.

Metabarcoding and metabolome analyses of copepod grazing reveal feeding preference and linkage to metabolite classes in dynamic microbial plankton communities.

PubMed

Ray, Jessica L; Althammer, Julia; Skaar, Katrine S; Simonelli, Paolo; Larsen, Aud; Stoecker, Diane; Sazhin, Andrey; Ijaz, Umer Z; Quince, Christopher; Nejstgaard, Jens C; Frischer, Marc; Pohnert, Georg; Troedsson, Christofer

2016-11-01

In order to characterize copepod feeding in relation to microbial plankton community dynamics, we combined metabarcoding and metabolome analyses during a 22-day seawater mesocosm experiment. Nutrient amendment of mesocosms promoted the development of haptophyte (Phaeocystis pouchetii)- and diatom (Skeletonema marinoi)-dominated plankton communities in mesocosms, in which Calanus sp. copepods were incubated for 24 h in flow-through chambers to allow access to prey particles (<500 μm). Copepods and mesocosm water sampled six times spanning the experiment were analysed using metabarcoding, while intracellular metabolite profiles of mesocosm plankton communities were generated for all experimental days. Taxon-specific metabarcoding ratios (ratio of consumed prey to available prey in the surrounding seawater) revealed diverse and dynamic copepod feeding selection, with positive selection on large diatoms, heterotrophic nanoflagellates and fungi, while smaller phytoplankton, including P. pouchetii, were passively consumed or even negatively selected according to our indicator. Our analysis of the relationship between Calanus grazing ratios and intracellular metabolite profiles indicates the importance of carbohydrates and lipids in plankton succession and copepod-prey interactions. This molecular characterization of Calanus sp. grazing therefore provides new evidence for selective feeding in mixed plankton assemblages and corroborates previous findings that copepod grazing may be coupled to the developmental and metabolic stage of the entire prey community rather than to individual prey abundances. © 2016 John Wiley & Sons Ltd.

Attractor Structures of Signaling Networks: Consequences of Different Conformational Barcode Dynamics and Their Relations to Network-Based Drug Design.

PubMed

Szalay, Kristóf Z; Nussinov, Ruth; Csermely, Peter

2014-06-01

Conformational barcodes tag functional sites of proteins and are decoded by interacting molecules transmitting the incoming signal. Conformational barcodes are modified by all co-occurring allosteric events induced by post-translational modifications, pathogen, drug binding, etc. We argue that fuzziness (plasticity) of conformational barcodes may be increased by disordered protein structures, by integrative plasticity of multi-phosphorylation events, by increased intracellular water content (decreased molecular crowding) and by increased action of molecular chaperones. This leads to increased plasticity of signaling and cellular networks. Increased plasticity is both substantiated by and inducing an increased noise level. Using the versatile network dynamics tool, Turbine (www.turbine.linkgroup.hu), here we show that the 10 % noise level expected in cellular systems shifts a cancer-related signaling network of human cells from its proliferative attractors to its largest, apoptotic attractor representing their health-preserving response in the carcinogen containing and tumor suppressor deficient environment modeled in our study. Thus, fuzzy conformational barcodes may not only make the cellular system more plastic, and therefore more adaptable, but may also stabilize the complex system allowing better access to its largest attractor. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Preparation time influences ankle and knee joint control during dynamic change of direction movements.

PubMed

Fuerst, Patrick; Gollhofer, Albert; Gehring, Dominic

2017-04-01

The influence of preparation time on ankle joint biomechanics during highly dynamic movements is largely unknown. The aim of this study was to evaluate the impact of limited preparation time on ankle joint loading during highly dynamic run-and-cut movements. Thirteen male basketball players performed 45°-sidestep-cutting and 180°-turning manoeuvres in reaction to light signals which appeared during the approach run. Both movements were executed under (1) an easy condition, in which the light signal appeared very early, (2) a medium condition and (3) a hard condition with very little time to prepare the movements. Maximum ankle inversion angles, moments and velocities during ground contact, as well as EMG signals of three lower extremity muscles, were analysed. In 180°-turning movements, reduced preparation time led to significantly increased maximum ankle inversion velocities. Muscular activation levels, however, did not change. Increased inversion velocities, without accompanying changes in muscular activation, may have the potential to destabilise the ankle joint when less preparation time is available. This may result in a higher injury risk during turning movements and should therefore be considered in ankle injury research and the aetiology of ankle sprains.

Processing oscillatory signals by incoherent feedforward loops

NASA Astrophysics Data System (ADS)

Zhang, Carolyn; Wu, Feilun; Tsoi, Ryan; Shats, Igor; You, Lingchong

From the timing of amoeba development to the maintenance of stem cell pluripotency,many biological signaling pathways exhibit the ability to differentiate between pulsatile and sustained signals in the regulation of downstream gene expression.While networks underlying this signal decoding are diverse,many are built around a common motif, the incoherent feedforward loop (IFFL),where an input simultaneously activates an output and an inhibitor of the output.With appropriate parameters,this motif can generate temporal adaptation,where the system is desensitized to a sustained input.This property serves as the foundation for distinguishing signals with varying temporal profiles.Here,we use quantitative modeling to examine another property of IFFLs,the ability to process oscillatory signals.Our results indicate that the system's ability to translate pulsatile dynamics is limited by two constraints.The kinetics of IFFL components dictate the input range for which the network can decode pulsatile dynamics.In addition,a match between the network parameters and signal characteristics is required for optimal ``counting''.We elucidate one potential mechanism by which information processing occurs in natural networks with implications in the design of synthetic gene circuits for this purpose. This work was partially supported by the National Science Foundation Graduate Research Fellowship (CZ).

Processing Oscillatory Signals by Incoherent Feedforward Loops

PubMed Central

Zhang, Carolyn; You, Lingchong

2016-01-01

From the timing of amoeba development to the maintenance of stem cell pluripotency, many biological signaling pathways exhibit the ability to differentiate between pulsatile and sustained signals in the regulation of downstream gene expression. While the networks underlying this signal decoding are diverse, many are built around a common motif, the incoherent feedforward loop (IFFL), where an input simultaneously activates an output and an inhibitor of the output. With appropriate parameters, this motif can exhibit temporal adaptation, where the system is desensitized to a sustained input. This property serves as the foundation for distinguishing input signals with varying temporal profiles. Here, we use quantitative modeling to examine another property of IFFLs—the ability to process oscillatory signals. Our results indicate that the system’s ability to translate pulsatile dynamics is limited by two constraints. The kinetics of the IFFL components dictate the input range for which the network is able to decode pulsatile dynamics. In addition, a match between the network parameters and input signal characteristics is required for optimal “counting”. We elucidate one potential mechanism by which information processing occurs in natural networks, and our work has implications in the design of synthetic gene circuits for this purpose. PMID:27623175

Performance of Stratified and Subgrouped Disproportionality Analyses in Spontaneous Databases.

PubMed

Seabroke, Suzie; Candore, Gianmario; Juhlin, Kristina; Quarcoo, Naashika; Wisniewski, Antoni; Arani, Ramin; Painter, Jeffery; Tregunno, Philip; Norén, G Niklas; Slattery, Jim

2016-04-01

Disproportionality analyses are used in many organisations to identify adverse drug reactions (ADRs) from spontaneous report data. Reporting patterns vary over time, with patient demographics, and between different geographical regions, and therefore subgroup analyses or adjustment by stratification may be beneficial. The objective of this study was to evaluate the performance of subgroup and stratified disproportionality analyses for a number of key covariates within spontaneous report databases of differing sizes and characteristics. Using a reference set of established ADRs, signal detection performance (sensitivity and precision) was compared for stratified, subgroup and crude (unadjusted) analyses within five spontaneous report databases (two company, one national and two international databases). Analyses were repeated for a range of covariates: age, sex, country/region of origin, calendar time period, event seriousness, vaccine/non-vaccine, reporter qualification and report source. Subgroup analyses consistently performed better than stratified analyses in all databases. Subgroup analyses also showed benefits in both sensitivity and precision over crude analyses for the larger international databases, whilst for the smaller databases a gain in precision tended to result in some loss of sensitivity. Additionally, stratified analyses did not increase sensitivity or precision beyond that associated with analytical artefacts of the analysis. The most promising subgroup covariates were age and region/country of origin, although this varied between databases. Subgroup analyses perform better than stratified analyses and should be considered over the latter in routine first-pass signal detection. Subgroup analyses are also clearly beneficial over crude analyses for larger databases, but further validation is required for smaller databases.

Quantitative measures for redox signaling.

PubMed

Pillay, Ché S; Eagling, Beatrice D; Driscoll, Scott R E; Rohwer, Johann M

2016-07-01

Redox signaling is now recognized as an important regulatory mechanism for a number of cellular processes including the antioxidant response, phosphokinase signal transduction and redox metabolism. While there has been considerable progress in identifying the cellular machinery involved in redox signaling, quantitative measures of redox signals have been lacking, limiting efforts aimed at understanding and comparing redox signaling under normoxic and pathogenic conditions. Here we have outlined some of the accepted principles for redox signaling, including the description of hydrogen peroxide as a signaling molecule and the role of kinetics in conferring specificity to these signaling events. Based on these principles, we then develop a working definition for redox signaling and review a number of quantitative methods that have been employed to describe signaling in other systems. Using computational modeling and published data, we show how time- and concentration- dependent analyses, in particular, could be used to quantitatively describe redox signaling and therefore provide important insights into the functional organization of redox networks. Finally, we consider some of the key challenges with implementing these methods. Copyright © 2016 Elsevier Inc. All rights reserved.

Comment on "A dynamic network model of mTOR signaling reveals TSC-independent mTORC2 regulation": building a model of the mTOR signaling network with a potentially faulty tool.

PubMed

Manning, Brendan D

2012-07-10

In their study published in Science Signaling (Research Article, 27 March 2012, DOI: 10.1126/scisignal.2002469), Dalle Pezze et al. tackle the dynamic and complex wiring of the signaling network involving the protein kinase mTOR, which exists within two distinct protein complexes (mTORC1 and mTORC2) that differ in their regulation and function. The authors use a combination of immunoblotting for specific phosphorylation events and computational modeling. The primary experimental tool employed is to monitor the autophosphorylation of mTOR on Ser(2481) in cell lysates as a surrogate for mTOR activity, which the authors conclude is a specific readout for mTORC2. However, Ser(2481) phosphorylation occurs on both mTORC1 and mTORC2 and will dynamically change as the network through which these two complexes are connected is manipulated. Therefore, models of mTOR network regulation built using this tool are inherently imperfect and open to alternative explanations. Specific issues with the main conclusion made in this study, involving the TSC1-TSC2 (tuberous sclerosis complex 1 and 2) complex and its potential regulation of mTORC2, are discussed here. A broader goal of this Letter is to clarify to other investigators the caveats of using mTOR Ser(2481) phosphorylation in cell lysates as a specific readout for either of the two mTOR complexes.

The Hedgehog Signal Transduction Network

PubMed Central

Robbins, David J.; Fei, Dennis Liang; Riobo, Natalia A.

2013-01-01

Hedgehog (Hh) proteins regulate the development of a wide range of metazoan embryonic and adult structures, and disruption of Hh signaling pathways results in various human diseases. Here, we provide a comprehensive review of the signaling pathways regulated by Hh, consolidating data from a diverse array of organisms in a variety of scientific disciplines. Similar to the elucidation of many other signaling pathways, our knowledge of Hh signaling developed in a sequential manner centered on its earliest discoveries. Thus, our knowledge of Hh signaling has for the most part focused on elucidating the mechanism by which Hh regulates the Gli family of transcription factors, the so-called “canonical” Hh signaling pathway. However, in the past few years, numerous studies have shown that Hh proteins can also signal through Gli-independent mechanisms collectively referred to as “noncanonical” signaling pathways. Noncanonical Hh signaling is itself subdivided into two distinct signaling modules: (i) those not requiring Smoothened (Smo) and (ii) those downstream of Smo that do not require Gli transcription factors. Thus, Hh signaling is now proposed to occur through a variety of distinct context-dependent signaling modules that have the ability to crosstalk with one another to form an interacting, dynamic Hh signaling network. PMID:23074268

Dynamics of Phosphoinositide-Dependent Signaling in Sympathetic Neurons

PubMed Central

Kruse, Martin; Vivas, Oscar; Traynor-Kaplan, Alexis

2016-01-01

In neurons, loss of plasma membrane phosphatidylinositol 4,5-bisphosphate [PI(4,5)P2] leads to a decrease in exocytosis and changes in electrical excitability. Restoration of PI(4,5)P2 levels after phospholipase C activation is therefore essential for a return to basal neuronal activity. However, the dynamics of phosphoinositide metabolism have not been analyzed in neurons. We measured dynamic changes of PI(4,5)P2, phosphatidylinositol 4-phosphate, diacylglycerol, inositol 1,4,5-trisphosphate, and Ca2+ upon muscarinic stimulation in sympathetic neurons from adult male Sprague-Dawley rats with electrophysiological and optical approaches. We used this kinetic information to develop a quantitative description of neuronal phosphoinositide metabolism. The measurements and analysis show and explain faster synthesis of PI(4,5)P2 in sympathetic neurons than in electrically nonexcitable tsA201 cells. They can be used to understand dynamic effects of receptor-mediated phospholipase C activation on excitability and other PI(4,5)P2-dependent processes in neurons. SIGNIFICANCE STATEMENT Phosphatidylinositol 4,5-bisphosphate [PI(4,5)P2] is a minor phospholipid in the cytoplasmic leaflet of the plasma membrane. Depletion of PI(4,5)P2 via phospholipase C-mediated hydrolysis leads to a decrease in exocytosis and alters electrical excitability in neurons. Restoration of PI(4,5)P2 is essential for a return to basal neuronal activity. However, the dynamics of phosphoinositide metabolism have not been analyzed in neurons. We studied the dynamics of phosphoinositide metabolism in sympathetic neurons upon muscarinic stimulation and used the kinetic information to develop a quantitative description of neuronal phosphoinositide metabolism. The measurements and analysis show a several-fold faster synthesis of PI(4,5)P2 in sympathetic neurons than in an electrically nonexcitable cell line, and provide a framework for future studies of PI(4,5)P2-dependent processes in neurons. PMID:26818524

Using Movies to Analyse Gene Circuit Dynamics in Single Cells

PubMed Central

Locke, James CW; Elowitz, Michael B

2010-01-01

Preface Many bacterial systems rely on dynamic genetic circuits to control critical processes. A major goal of systems biology is to understand these behaviours in terms of individual genes and their interactions. However, traditional techniques based on population averages wash out critical dynamics that are either unsynchronized between cells or driven by fluctuations, or ‘noise,’ in cellular components. Recently, the combination of time-lapse microscopy, quantitative image analysis, and fluorescent protein reporters has enabled direct observation of multiple cellular components over time in individual cells. In conjunction with mathematical modelling, these techniques are now providing powerful insights into genetic circuit behaviour in diverse microbial systems. PMID:19369953

Dynamical Structure of Madden-Julian Oscillation over Malay Peninsula

NASA Astrophysics Data System (ADS)

Djamil, Y. S.; Koh, T. Y.; Chandimala, J.; Teo, C. K.

2014-12-01

Madden-Julian Oscillation (MJO) is the dominant weather event in the intraseasonal time scale over Malay Peninsula region. The MJO signals are represented by the first two modes of radiosonde records extracted using Extended Empirical Orthogonal Function (EEOF) analyses which we label as Local Multivariate MJO (LMM). LMM is able to capture the spatio-temporal profile of MJO along the global tropics in all seasons. With the help of LMM, we clarify the dynamical and thermodynamical structure of the MJO over Malay Peninsula, including the unique "boomerang-shaped" feature in the time-height temperature profile identified in previous literature.

Rho-associated coiled-coil kinase (ROCK) protein controls microtubule dynamics in a novel signaling pathway that regulates cell migration.

PubMed

Schofield, Alice V; Steel, Rohan; Bernard, Ora

2012-12-21

The two members of the Rho-associated coiled-coil kinase (ROCK1 and 2) family are established regulators of actin dynamics that are involved in the regulation of the cell cycle as well as cell motility and invasion. Here, we discovered a novel signaling pathway whereby ROCK regulates microtubule (MT) acetylation via phosphorylation of the tubulin polymerization promoting protein 1 (TPPP1/p25). We show that ROCK phosphorylation of TPPP1 inhibits the interaction between TPPP1 and histone deacetylase 6 (HDAC6), which in turn results in increased HDAC6 activity followed by a decrease in MT acetylation. As a consequence, we show that TPPP1 phosphorylation by ROCK increases cell migration and invasion via modulation of cellular acetyl MT levels. We establish here that the ROCK-TPPP1-HDAC6 signaling pathway is important for the regulation of cell migration and invasion.

Insights into soil carbon dynamics across climatic gradients from carbon-pool specific radiocarbon analyses

NASA Astrophysics Data System (ADS)

van der Voort, Tessa Sophia; Hagedorn, Frank; McIntyre, Cameron; Zell, Claudia; Eglinton, Timothy Ian

2017-04-01

Soil carbon constitutes the largest terrestrial reservoir of organic carbon, and therefore understanding the mechanisms and drivers of carbon stabilization is crucial, especially in the framework of climate change. The understanding of the dependence of soil organic turnover in specific carbon pools as related to e.g. climate, soil texture and mineralogy is limited. In this framework, radiocarbon constitutes a uniquely powerful tool that help to unravel carbon dynamics from decadal to millennial timescales. This project combines bulk and pool-specific radiocarbon analyses in the top and deep soil on a wide range of forested soils that span a large climatic gradient (MAT 1.3-9.2°C, MAP 600 to 2100 mm m-2y-1). These well-studies sites are part of the Long-Term Forest Ecosystem Research (LWF) program of the Swiss Federal Institute for Forest, Snow and Landscape research (WSL). This study aims to combine the insights gained from bulk and pool-specific turnover to environmental conditions and molecular composition of soil carbon. The pools investigated span the mineral-associated (occluded and heavy fractions from density fractionation) and potentially water-soluble (free light fractions from density fractionation and water extractable organic carbon) organic carbon fractions. Pool-specific radiocarbon work is augmented by the measurement of abundance of compounds such as alkanes, fatty acids and lignin phenols on a subset of samples. Initial results show disparate patterns depending on soil type and in particular soil texture, which could be indicative of various stabilization mechanisms in different soils. Overall, this study provides new insights into the controls of soil organic matter dynamics as related to environmental conditions, in particular in specific sub-pools of carbon.

AMA- and RWE- Based Adaptive Kalman Filter for Denoising Fiber Optic Gyroscope Drift Signal.

PubMed

Yang, Gongliu; Liu, Yuanyuan; Li, Ming; Song, Shunguang

2015-10-23

An improved double-factor adaptive Kalman filter called AMA-RWE-DFAKF is proposed to denoise fiber optic gyroscope (FOG) drift signal in both static and dynamic conditions. The first factor is Kalman gain updated by random weighting estimation (RWE) of the covariance matrix of innovation sequence at any time to ensure the lowest noise level of output, but the inertia of KF response increases in dynamic condition. To decrease the inertia, the second factor is the covariance matrix of predicted state vector adjusted by RWE only when discontinuities are detected by adaptive moving average (AMA).The AMA-RWE-DFAKF is applied for denoising FOG static and dynamic signals, its performance is compared with conventional KF (CKF), RWE-based adaptive KF with gain correction (RWE-AKFG), AMA- and RWE- based dual mode adaptive KF (AMA-RWE-DMAKF). Results of Allan variance on static signal and root mean square error (RMSE) on dynamic signal show that this proposed algorithm outperforms all the considered methods in denoising FOG signal.

Speaking and Listening with the Eyes: Gaze Signaling during Dyadic Interactions.

PubMed

Ho, Simon; Foulsham, Tom; Kingstone, Alan

2015-01-01

Cognitive scientists have long been interested in the role that eye gaze plays in social interactions. Previous research suggests that gaze acts as a signaling mechanism and can be used to control turn-taking behaviour. However, early research on this topic employed methods of analysis that aggregated gaze information across an entire trial (or trials), which masks any temporal dynamics that may exist in social interactions. More recently, attempts have been made to understand the temporal characteristics of social gaze but little research has been conducted in a natural setting with two interacting participants. The present study combines a temporally sensitive analysis technique with modern eye tracking technology to 1) validate the overall results from earlier aggregated analyses and 2) provide insight into the specific moment-to-moment temporal characteristics of turn-taking behaviour in a natural setting. Dyads played two social guessing games (20 Questions and Heads Up) while their eyes were tracked. Our general results are in line with past aggregated data, and using cross-correlational analysis on the specific gaze and speech signals of both participants we found that 1) speakers end their turn with direct gaze at the listener and 2) the listener in turn begins to speak with averted gaze. Convergent with theoretical models of social interaction, our data suggest that eye gaze can be used to signal both the end and the beginning of a speaking turn during a social interaction. The present study offers insight into the temporal dynamics of live dyadic interactions and also provides a new method of analysis for eye gaze data when temporal relationships are of interest.

Speaking and Listening with the Eyes: Gaze Signaling during Dyadic Interactions

PubMed Central

Ho, Simon; Foulsham, Tom; Kingstone, Alan

2015-01-01

Cognitive scientists have long been interested in the role that eye gaze plays in social interactions. Previous research suggests that gaze acts as a signaling mechanism and can be used to control turn-taking behaviour. However, early research on this topic employed methods of analysis that aggregated gaze information across an entire trial (or trials), which masks any temporal dynamics that may exist in social interactions. More recently, attempts have been made to understand the temporal characteristics of social gaze but little research has been conducted in a natural setting with two interacting participants. The present study combines a temporally sensitive analysis technique with modern eye tracking technology to 1) validate the overall results from earlier aggregated analyses and 2) provide insight into the specific moment-to-moment temporal characteristics of turn-taking behaviour in a natural setting. Dyads played two social guessing games (20 Questions and Heads Up) while their eyes were tracked. Our general results are in line with past aggregated data, and using cross-correlational analysis on the specific gaze and speech signals of both participants we found that 1) speakers end their turn with direct gaze at the listener and 2) the listener in turn begins to speak with averted gaze. Convergent with theoretical models of social interaction, our data suggest that eye gaze can be used to signal both the end and the beginning of a speaking turn during a social interaction. The present study offers insight into the temporal dynamics of live dyadic interactions and also provides a new method of analysis for eye gaze data when temporal relationships are of interest. PMID:26309216

Early Warning Signals of Financial Crises with Multi-Scale Quantile Regressions of Log-Periodic Power Law Singularities

PubMed Central

Zhang, Qun; Zhang, Qunzhi; Sornette, Didier

2016-01-01

We augment the existing literature using the Log-Periodic Power Law Singular (LPPLS) structures in the log-price dynamics to diagnose financial bubbles by providing three main innovations. First, we introduce the quantile regression to the LPPLS detection problem. This allows us to disentangle (at least partially) the genuine LPPLS signal and the a priori unknown complicated residuals. Second, we propose to combine the many quantile regressions with a multi-scale analysis, which aggregates and consolidates the obtained ensembles of scenarios. Third, we define and implement the so-called DS LPPLS Confidence™ and Trust™ indicators that enrich considerably the diagnostic of bubbles. Using a detailed study of the “S&P 500 1987” bubble and presenting analyses of 16 historical bubbles, we show that the quantile regression of LPPLS signals contributes useful early warning signals. The comparison between the constructed signals and the price development in these 16 historical bubbles demonstrates their significant predictive ability around the real critical time when the burst/rally occurs. PMID:27806093

Interactions of Ku70/80 with Double-Strand DNA: Energetic, Dynamics, and Functional Implications

NASA Technical Reports Server (NTRS)

Hu, Shaowen; Cucinotta, Francis A.

2010-01-01

Space radiation is a proficient inducer of DNA damage leading to mutation, aberrant cell signaling, and cancer formation. Ku is among the first responding proteins in nucleus to recognize and bind the DNA double strand breaks (DSBs) whenever they are introduced. Once loaded Ku works as a scaffold to recruit other repair factors of non-homologous end joining and facilitates the following repair processes. The crystallographic study of the Ku70/80 heterodimer indicate the core structure of this protein shows virtually no conformational change after binding with DNA. To investigate the dynamical features as well as the energetic characteristics of Ku-DNA binding, we conduct multi-nanosecond molecular dynamics simulations of a modeled Ku70/80 structure and several complexes with two 24-bp DNA duplexes. Free energy calculations show significant energy differences between the complexes with Ku bound at DSBs and those with Ku associated at an internal site of a chromosome. The results also reveal detailed interactions between different nucleotides and the amino acids along the DNA-binding cradle of Ku, indicating subtle binding preference of Ku at specific DNA sequences. The covariance matrix analyses along the trajectories demonstrate the protein is stimulated to undergo correlated motions of different domains once bound to DNA ends. Additionally, principle component analyses identify these low frequency collective motions suitable for binding with and translocation along duplex DNA. It is proposed that the modification of dynamical properties of Ku upon binding with DSBs may provide a signal for the further recruitment of other repair factors such as DNA-PKcs, XLF, and XRCC4.

Statistical errors in molecular dynamics averages

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schiferl, S.K.; Wallace, D.C.

1985-11-15

A molecular dynamics calculation produces a time-dependent fluctuating signal whose average is a thermodynamic quantity of interest. The average of the kinetic energy, for example, is proportional to the temperature. A procedure is described for determining when the molecular dynamics system is in equilibrium with respect to a given variable, according to the condition that the mean and the bandwidth of the signal should be sensibly constant in time. Confidence limits for the mean are obtained from an analysis of a finite length of the equilibrium signal. The role of serial correlation in this analysis is discussed. The occurence ofmore » unstable behavior in molecular dynamics data is noted, and a statistical test for a level shift is described.« less

Signalling and obfuscation for congestion control

NASA Astrophysics Data System (ADS)

Mareček, Jakub; Shorten, Robert; Yu, Jia Yuan

2015-10-01

We aim to reduce the social cost of congestion in many smart city applications. In our model of congestion, agents interact over limited resources after receiving signals from a central agent that observes the state of congestion in real time. Under natural models of agent populations, we develop new signalling schemes and show that by introducing a non-trivial amount of uncertainty in the signals, we reduce the social cost of congestion, i.e., improve social welfare. The signalling schemes are efficient in terms of both communication and computation, and are consistent with past observations of the congestion. Moreover, the resulting population dynamics converge under reasonable assumptions.

Inferring neural activity from BOLD signals through nonlinear optimization.

PubMed

Vakorin, Vasily A; Krakovska, Olga O; Borowsky, Ron; Sarty, Gordon E

2007-11-01

The blood oxygen level-dependent (BOLD) fMRI signal does not measure neuronal activity directly. This fact is a key concern for interpreting functional imaging data based on BOLD. Mathematical models describing the path from neural activity to the BOLD response allow us to numerically solve the inverse problem of estimating the timing and amplitude of the neuronal activity underlying the BOLD signal. In fact, these models can be viewed as an advanced substitute for the impulse response function. In this work, the issue of estimating the dynamics of neuronal activity from the observed BOLD signal is considered within the framework of optimization problems. The model is based on the extended "balloon" model and describes the conversion of neuronal signals into the BOLD response through the transitional dynamics of the blood flow-inducing signal, cerebral blood flow, cerebral blood volume and deoxyhemoglobin concentration. Global optimization techniques are applied to find a control input (the neuronal activity and/or the biophysical parameters in the model) that causes the system to follow an admissible solution to minimize discrepancy between model and experimental data. As an alternative to a local linearization (LL) filtering scheme, the optimization method escapes the linearization of the transition system and provides a possibility to search for the global optimum, avoiding spurious local minima. We have found that the dynamics of the neural signals and the physiological variables as well as the biophysical parameters can be robustly reconstructed from the BOLD responses. Furthermore, it is shown that spiking off/on dynamics of the neural activity is the natural mathematical solution of the model. Incorporating, in addition, the expansion of the neural input by smooth basis functions, representing a low-pass filtering, allows us to model local field potential (LFP) solutions instead of spiking solutions.

The Evolution of Covert Signaling.

PubMed

Smaldino, Paul E; Flamson, Thomas J; McElreath, Richard

2018-03-20

Human sociality depends upon the benefits of mutual aid and extensive communication. However, diverse norms and preferences complicate mutual aid, and ambiguity in meaning hinders communication. Here we demonstrate that these two problems can work together to enhance cooperation through the strategic use of deliberately ambiguous signals: covert signaling. Covert signaling is the transmission of information that is accurately received by its intended audience but obscured when perceived by others. Such signals may allow coordination and enhanced cooperation while also avoiding the alienation or hostile reactions of individuals with different preferences. Although the empirical literature has identified potential mechanisms of covert signaling, such as encryption in humor, there is to date no formal theory of its dynamics. We introduce a novel mathematical model to assess when a covert signaling strategy will evolve, as well as how receiver attitudes coevolve with covert signals. Covert signaling plausibly serves an important function in facilitating within-group cooperative assortment by allowing individuals to pair up with similar group members when possible and to get along with dissimilar ones when necessary. This mechanism has broad implications for theories of signaling and cooperation, humor, social identity, political psychology, and the evolution of human cultural complexity.

Structure-based Reassessment of the Caveolin Signaling Model: Do Caveolae Regulate Signaling Through Caveolin-Protein Interactions?

PubMed Central

Collins, Brett M.; Davis, Melissa J.; Hancock, John F.; Parton, Robert G.

2012-01-01

Summary Caveolin proteins drive formation of caveolae, specialized cell-surface microdomains that influence cell signaling. Signaling proteins are proposed to use conserved caveolin-binding motifs (CBMs) to associate with caveolae via the caveolin scaffolding domain (CSD). However, structural and bioinformatic analyses argue against such direct physical interactions: In the majority of signaling proteins, the CBM is buried and inaccessible. Putative CBMs do not form a common structure for caveolin recognition, are not enriched amongst caveolin-binding proteins, and are even more common in yeast, which lack caveolae. We propose that CBM/CSD-dependent interactions are unlikely to mediate caveolar signaling, and the basis for signaling effects should therefore be reassessed. PMID:22814599

The Role of Target of Rapamycin Signaling Networks in Plant Growth and Metabolism1

PubMed Central

Sheen, Jen

2014-01-01

The target of rapamycin (TOR) kinase, a master regulator that is evolutionarily conserved among yeasts (Saccharomyces cerevisiae), plants, animals, and humans, integrates nutrient and energy signaling to promote cell proliferation and growth. Recent breakthroughs made possible by integrating chemical, genetic, and genomic analyses have greatly increased our understanding of the molecular functions and dynamic regulation of the TOR kinase in photosynthetic plants. TOR signaling plays fundamental roles in embryogenesis, meristem activation, root and leaf growth, flowering, senescence, and life span determination. The molecular mechanisms underlying TOR-mediated ribosomal biogenesis, translation promotion, readjustment of metabolism, and autophagy inhibition are now being uncovered. Moreover, monitoring photosynthesis-derived Glc and bioenergetics relays has revealed that TOR orchestrates unprecedented transcriptional networks that wire central metabolism and biosynthesis for energy and biomass production. In addition, these networks integrate localized stem/progenitor cell proliferation through interorgan nutrient coordination to control developmental transitions and growth. PMID:24385567

Network coding based joint signaling and dynamic bandwidth allocation scheme for inter optical network unit communication in passive optical networks

NASA Astrophysics Data System (ADS)

Wei, Pei; Gu, Rentao; Ji, Yuefeng

2014-06-01

As an innovative and promising technology, network coding has been introduced to passive optical networks (PON) in recent years to support inter optical network unit (ONU) communication, yet the signaling process and dynamic bandwidth allocation (DBA) in PON with network coding (NC-PON) still need further study. Thus, we propose a joint signaling and DBA scheme for efficiently supporting differentiated services of inter ONU communication in NC-PON. In the proposed joint scheme, the signaling process lays the foundation to fulfill network coding in PON, and it can not only avoid the potential threat to downstream security in previous schemes but also be suitable for the proposed hybrid dynamic bandwidth allocation (HDBA) scheme. In HDBA, a DBA cycle is divided into two sub-cycles for applying different coding, scheduling and bandwidth allocation strategies to differentiated classes of services. Besides, as network traffic load varies, the entire upstream transmission window for all REPORT messages slides accordingly, leaving the transmission time of one or two sub-cycles to overlap with the bandwidth allocation calculation time at the optical line terminal (the OLT), so that the upstream idle time can be efficiently eliminated. Performance evaluation results validate that compared with the existing two DBA algorithms deployed in NC-PON, HDBA demonstrates the best quality of service (QoS) support in terms of delay for all classes of services, especially guarantees the end-to-end delay bound of high class services. Specifically, HDBA can eliminate queuing delay and scheduling delay of high class services, reduce those of lower class services by at least 20%, and reduce the average end-to-end delay of all services over 50%. Moreover, HDBA also achieves the maximum delay fairness between coded and uncoded lower class services, and medium delay fairness for high class services.

Global Picosecond Structural Dynamics of Orange Carotenoid Protein in Photo/Chemical Activated Signaling States

NASA Astrophysics Data System (ADS)

Deng, Yanting; Xu, Mengyang; Liu, Hanjun; Blankenship, Robert; Markelz, Andrea

Light availability to photosynthetic organisms changes throughout the day. High light can over-saturate photosynthetic capacity and produce reactive oxygen which damages the photosynthetic apparatus and leads to cell death. Photosynthetic organisms have evolved multiple photo-protective strategies to prevent oxidative damage from light stress. For cyanobacteria, a blue-light photo-sensor orange carotenoid protein (OCP) responds to exposure to intense light. Upon high light stress, OCP converts from the orange inactive form (OCPO) to the red active form (OCPR) , with a large conformational change. And OCPR interacts with the light harvesting antenna phycobilisome (PB), and mediates the energy quenching of PB. We argue that both the susceptibility of OCP to large conformational change and its interaction with PB are associated with changes in the long range picosecond structural flexibility. To investigate the protein flexibility with signaling state dependence, temperature dependent terahertz time domain spectroscopy is performed in the range of 80 - 290 K on OCP solutions, as a function of illumination and chaotrope (NaSCN) concentration, which produces a long lived red state in the absence of photoexcitation. We characterize the global flexibility by both the net THz absorbance and the dynamical transition temperature, which scales with structural stability, and observed the dynamical transition occurred in the 180-220 K range. R.E.B. acknowledges DOE award DE-FG02- 07ER15902 and A.G.M. acknowledges NSF awards DBI 1556359 and MCB 1616529, and DOE award DE-SC0016317 for support of the work.

Signal Analysis for Aerosat.

DOT National Transportation Integrated Search

1972-08-01

The report addresses signal design for the AEROSAT system. Candidate data and surveillance modems are analyzed for L-Band avionics. Detailed theoretical analyses are presented of the effects of the oceanic satellite-aircraft channel on data modem per...

Estradiol Membrane-Initiated Signaling in the Brain Mediates Reproduction.

PubMed

Micevych, Paul E; Mermelstein, Paul G; Sinchak, Kevin

2017-11-01

Over the past few years our understanding of estrogen signaling in the brain has expanded rapidly. Estrogens are synthesized in the periphery and in the brain, acting on multiple receptors to regulate gene transcription, neural function, and behavior. Various estrogen-sensitive signaling pathways often operate in concert within the same cell, increasing the complexity of the system. In females, estrogen concentrations fluctuate over the estrous/menstrual cycle, dynamically modulating estrogen receptor (ER) expression, activity, and trafficking. These dynamic changes influence multiple behaviors but are particularly important for reproduction. Using the female rodent model, we review our current understanding of estradiol signaling in the regulation of sexual receptivity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Structural Dynamics in Ras and Related Proteins upon Nucleotide Switching.

PubMed

Harrison, Rane A; Lu, Jia; Carrasco, Martin; Hunter, John; Manandhar, Anuj; Gondi, Sudershan; Westover, Kenneth D; Engen, John R

2016-11-20

Structural dynamics of Ras proteins contributes to their activity in signal transduction cascades. Directly targeting Ras proteins with small molecules may rely on the movement of a conserved structural motif, switch II. To understand Ras signaling and advance Ras-targeting strategies, experimental methods to measure Ras dynamics are required. Here, we demonstrate the utility of hydrogen-deuterium exchange (HDX) mass spectrometry (MS) to measure Ras dynamics by studying representatives from two branches of the Ras superfamily, Ras and Rho. A comparison of differential deuterium exchange between active (GMPPNP-bound) and inactive (GDP-bound) proteins revealed differences between the families, with the most notable differences occurring in the phosphate-binding loop and switch II. The P-loop exchange signature correlated with switch II dynamics observed in molecular dynamics simulations focused on measuring main-chain movement. HDX provides a means of evaluating Ras protein dynamics, which may be useful for understanding the mechanisms of Ras signaling, including activated signaling of pathologic mutants, and for targeting strategies that rely on protein dynamics. Copyright © 2016 Elsevier Ltd. All rights reserved.

Noise facilitates transcriptional control under dynamic inputs.

PubMed

Kellogg, Ryan A; Tay, Savaş

2015-01-29

Cells must respond sensitively to time-varying inputs in complex signaling environments. To understand how signaling networks process dynamic inputs into gene expression outputs and the role of noise in cellular information processing, we studied the immune pathway NF-κB under periodic cytokine inputs using microfluidic single-cell measurements and stochastic modeling. We find that NF-κB dynamics in fibroblasts synchronize with oscillating TNF signal and become entrained, leading to significantly increased NF-κB oscillation amplitude and mRNA output compared to non-entrained response. Simulations show that intrinsic biochemical noise in individual cells improves NF-κB oscillation and entrainment, whereas cell-to-cell variability in NF-κB natural frequency creates population robustness, together enabling entrainment over a wider range of dynamic inputs. This wide range is confirmed by experiments where entrained cells were measured under all input periods. These results indicate that synergy between oscillation and noise allows cells to achieve efficient gene expression in dynamically changing signaling environments. Copyright © 2015 Elsevier Inc. All rights reserved.

Light exposure at night disrupts host/cancer circadian regulatory dynamics: impact on the Warburg effect, lipid signaling and tumor growth prevention.

PubMed

Blask, David E; Dauchy, Robert T; Dauchy, Erin M; Mao, Lulu; Hill, Steven M; Greene, Michael W; Belancio, Victoria P; Sauer, Leonard A; Davidson, Leslie

2014-01-01

The central circadian clock within the suprachiasmatic nucleus (SCN) plays an important role in temporally organizing and coordinating many of the processes governing cancer cell proliferation and tumor growth in synchrony with the daily light/dark cycle which may contribute to endogenous cancer prevention. Bioenergetic substrates and molecular intermediates required for building tumor biomass each day are derived from both aerobic glycolysis (Warburg effect) and lipid metabolism. Using tissue-isolated human breast cancer xenografts grown in nude rats, we determined that circulating systemic factors in the host and the Warburg effect, linoleic acid uptake/metabolism and growth signaling activities in the tumor are dynamically regulated, coordinated and integrated within circadian time structure over a 24-hour light/dark cycle by SCN-driven nocturnal pineal production of the anticancer hormone melatonin. Dim light at night (LAN)-induced melatonin suppression disrupts this circadian-regulated host/cancer balance among several important cancer preventative signaling mechanisms, leading to hyperglycemia and hyperinsulinemia in the host and runaway aerobic glycolysis, lipid signaling and proliferative activity in the tumor.

Modularized TGFbeta-Smad Signaling Pathway

NASA Technical Reports Server (NTRS)

Li, Yongfeng; Wang, M.; Carra, C.; Cucinotta, F. A.

2011-01-01

The Transforming Growth Factor beta (TGFbeta) signaling pathway is a prominent regulatory signaling pathway controlling various important cellular processes. It can be induced by several factors, including ionizing radiation. It is regulated by Smads in a negative feedback loop through promoting increases in the regulatory Smads in the cell nucleus, and subsequent expression of inhibitory Smad, Smad7 to form a ubiquitin ligase with Smurf targeting active TGF receptors for degradation. In this work, we proposed a mathematical model to study the radiation-induced Smad-regulated TGF signaling pathway. By modularization, we are able to analyze each module (subsystem) and recover the nonlinear dynamics of the entire network system. Meanwhile the excitability, a common feature observed in the biological systems, along the TGF signaling pathway is discussed by mathematical analysis and numerical simulation.

Usage Autocorrelation Function in the Capacity of Indicator Shape of the Signal in Acoustic Emission Testing of Intricate Castings

NASA Astrophysics Data System (ADS)

Popkov, Artem

2016-01-01

The article contains information about acoustic emission signals analysing using autocorrelation function. Operation factors were analysed, such as shape of signal, the origins time and carrier frequency. The purpose of work is estimating the validity of correlations methods analysing signals. Acoustic emission signal consist of different types of waves, which propagate on different trajectories in object of control. Acoustic emission signal is amplitude-, phase- and frequency-modeling signal. It was described by carrier frequency at a given point of time. Period of signal make up 12.5 microseconds and carrier frequency make up 80 kHz for analysing signal. Usage autocorrelation function like indicator the origin time of acoustic emission signal raises validity localization of emitters.

Hilbert-Huang Transformation Based Analyses of FP1, FP2, and Fz Electroencephalogram Signals in Alcoholism.

PubMed

Lin, Chin-Feng; Su, Jiun-Yi; Wang, Hao-Min

2015-09-01

Chronic alcoholism may damage the central nervous system, causing imbalance in the excitation-inhibition homeostasis in the cortex, which may lead to hyper-arousal of the central nervous system, and impairments in cognitive function. In this paper, we use the Hilbert-Huang transformation (HHT) method to analyze the electroencephalogram (EEG) signals from control and alcoholic observers who watched two different pictures. We examined the intrinsic mode function (IMF) based energy distribution features of FP1, FP2, and Fz EEG signals in the time and frequency domains for alcoholics. The HHT-based characteristics of the IMFs, the instantaneous frequencies, and the time-frequency-energy distributions of the IMFs of the clinical FP1, FP2, and Fz EEG signals recorded from normal and alcoholic observers who watched two different pictures were analyzed. We observed that the number of peak amplitudes of the alcoholic subjects is larger than that of the control. In addition, the Pearson correlation coefficients of the IMFs, and the energy-IMF distributions of the clinical FP1, FP2, and Fz EEG signals recorded from normal and alcoholic observers were analyzed. The analysis results show that the energy ratios of IMF4, IMF5, and IMF7 waves of the normal observers to the refereed total energy were larger than 10 %, respectively. In addition, the energy ratios of IMF3, IMF4, and IMF5 waves of the alcoholic observers to the refereed total energy were larger than 10 %. The FP1 and FP2 waves of the normal observers, the FP1 and FP2 waves of the alcoholic observers, and the FP1 and Fz waves of the alcoholic observers demonstrated extremely high correlations. On the other hand, the FP1 waves of the normal and alcoholic observers, the FP1 wave of the normal observer and the FP2 wave of the alcoholic observer, the FP1 wave of the normal observer and the Fz wave of the alcoholic observer, the FP2 waves of the normal and alcoholic FP2 observers, and the FP2 wave of the normal observer and

Dynamic optimization of open-loop input signals for ramp-up current profiles in tokamak plasmas

NASA Astrophysics Data System (ADS)

Ren, Zhigang; Xu, Chao; Lin, Qun; Loxton, Ryan; Teo, Kok Lay

2016-03-01

Establishing a good current spatial profile in tokamak fusion reactors is crucial to effective steady-state operation. The evolution of the current spatial profile is related to the evolution of the poloidal magnetic flux, which can be modeled in the normalized cylindrical coordinates using a parabolic partial differential equation (PDE) called the magnetic diffusion equation. In this paper, we consider the dynamic optimization problem of attaining the best possible current spatial profile during the ramp-up phase of the tokamak. We first use the Galerkin method to obtain a finite-dimensional ordinary differential equation (ODE) model based on the original magnetic diffusion PDE. Then, we combine the control parameterization method with a novel time-scaling transformation to obtain an approximate optimal parameter selection problem, which can be solved using gradient-based optimization techniques such as sequential quadratic programming (SQP). This control parameterization approach involves approximating the tokamak input signals by piecewise-linear functions whose slopes and break-points are decision variables to be optimized. We show that the gradient of the objective function with respect to the decision variables can be computed by solving an auxiliary dynamic system governing the state sensitivity matrix. Finally, we conclude the paper with simulation results for an example problem based on experimental data from the DIII-D tokamak in San Diego, California.

Hippo signaling: growth control and beyond

PubMed Central

Halder, Georg; Johnson, Randy L.

2011-01-01

The Hippo pathway has emerged as a conserved signaling pathway that is essential for the proper regulation of organ growth in Drosophila and vertebrates. Although the mechanisms of signal transduction of the core kinases Hippo/Mst and Warts/Lats are relatively well understood, less is known about the upstream inputs of the pathway and about the downstream cellular and developmental outputs. Here, we review recently discovered mechanisms that contribute to the dynamic regulation of Hippo signaling during Drosophila and vertebrate development. We also discuss the expanding diversity of Hippo signaling functions during development, discoveries that shed light on a complex regulatory system and provide exciting new insights into the elusive mechanisms that regulate organ growth and regeneration. PMID:21138973

AMA- and RWE- Based Adaptive Kalman Filter for Denoising Fiber Optic Gyroscope Drift Signal

PubMed Central

Yang, Gongliu; Liu, Yuanyuan; Li, Ming; Song, Shunguang

2015-01-01

An improved double-factor adaptive Kalman filter called AMA-RWE-DFAKF is proposed to denoise fiber optic gyroscope (FOG) drift signal in both static and dynamic conditions. The first factor is Kalman gain updated by random weighting estimation (RWE) of the covariance matrix of innovation sequence at any time to ensure the lowest noise level of output, but the inertia of KF response increases in dynamic condition. To decrease the inertia, the second factor is the covariance matrix of predicted state vector adjusted by RWE only when discontinuities are detected by adaptive moving average (AMA).The AMA-RWE-DFAKF is applied for denoising FOG static and dynamic signals, its performance is compared with conventional KF (CKF), RWE-based adaptive KF with gain correction (RWE-AKFG), AMA- and RWE- based dual mode adaptive KF (AMA-RWE-DMAKF). Results of Allan variance on static signal and root mean square error (RMSE) on dynamic signal show that this proposed algorithm outperforms all the considered methods in denoising FOG signal. PMID:26512665

Influence of the piezoelectric parameters on the dynamics of an active rotor

NASA Astrophysics Data System (ADS)

Gawryluk, Jarosław; Mitura, Andrzej; Teter, Andrzej

2018-01-01

The main aim of this paper is an experimental and numerical analysis of the dynamic behavior of an active rotor with three composite blades. The study focuses on developing an effective FE modeling technique of a macro fiber composite element (denoted as MFC or active element) for the dynamic tests of active structures. The active rotor under consideration consists of a hub with a drive shaft, three grips and three glass-epoxy laminate blades with embedded active elements. A simplified FE model of the macro fiber composite element exhibiting the d33 piezoelectric effect is developed using the Abaqus software package. The discussed transducer is modeled as quasi-homogeneous piezoelectric material, and voltage is applied to the opposite faces of the element. In this case, the effective (equivalent) piezoelectric constant d33* is specified. Both static and dynamic tests are performed to verify the proposed model. First, static deflections of the active blade caused by the voltage signal are determined by numerical and experimental analyses. Next, a numerical modal analysis of the active rotor is performed. The eigenmodes and corresponding eigenfrequencies are determined by the Lanczos method. The influence of the model parameters (i.e., the effective piezoelectric constant d33 *, voltage signal, angular velocity) on the dynamics of the active rotor is examined. Finally, selected numerical results are validated in experimental tests. The experimental findings demonstrate that the structural stiffening effect caused by the active element strongly depends on the value of the effective piezoelectric constant.

Classifying acoustic signals into phoneme categories: average and dyslexic readers make use of complex dynamical patterns and multifractal scaling properties of the speech signal

PubMed Central

2015-01-01

Several competing aetiologies of developmental dyslexia suggest that the problems with acquiring literacy skills are causally entailed by low-level auditory and/or speech perception processes. The purpose of this study is to evaluate the diverging claims about the specific deficient peceptual processes under conditions of strong inference. Theoretically relevant acoustic features were extracted from a set of artificial speech stimuli that lie on a /bAk/-/dAk/ continuum. The features were tested on their ability to enable a simple classifier (Quadratic Discriminant Analysis) to reproduce the observed classification performance of average and dyslexic readers in a speech perception experiment. The ‘classical’ features examined were based on component process accounts of developmental dyslexia such as the supposed deficit in Envelope Rise Time detection and the deficit in the detection of rapid changes in the distribution of energy in the frequency spectrum (formant transitions). Studies examining these temporal processing deficit hypotheses do not employ measures that quantify the temporal dynamics of stimuli. It is shown that measures based on quantification of the dynamics of complex, interaction-dominant systems (Recurrence Quantification Analysis and the multifractal spectrum) enable QDA to classify the stimuli almost identically as observed in dyslexic and average reading participants. It seems unlikely that participants used any of the features that are traditionally associated with accounts of (impaired) speech perception. The nature of the variables quantifying the temporal dynamics of the speech stimuli imply that the classification of speech stimuli cannot be regarded as a linear aggregate of component processes that each parse the acoustic signal independent of one another, as is assumed by the ‘classical’ aetiologies of developmental dyslexia. It is suggested that the results imply that the differences in speech perception performance between

Contemporary ultrasonic signal processing approaches for nondestructive evaluation of multilayered structures

NASA Astrophysics Data System (ADS)

Zhang, Guang-Ming; Harvey, David M.

2012-03-01

Various signal processing techniques have been used for the enhancement of defect detection and defect characterisation. Cross-correlation, filtering, autoregressive analysis, deconvolution, neural network, wavelet transform and sparse signal representations have all been applied in attempts to analyse ultrasonic signals. In ultrasonic nondestructive evaluation (NDE) applications, a large number of materials have multilayered structures. NDE of multilayered structures leads to some specific problems, such as penetration, echo overlap, high attenuation and low signal-to-noise ratio. The signals recorded from a multilayered structure are a class of very special signals comprised of limited echoes. Such signals can be assumed to have a sparse representation in a proper signal dictionary. Recently, a number of digital signal processing techniques have been developed by exploiting the sparse constraint. This paper presents a review of research to date, showing the up-to-date developments of signal processing techniques made in ultrasonic NDE. A few typical ultrasonic signal processing techniques used for NDE of multilayered structures are elaborated. The practical applications and limitations of different signal processing methods in ultrasonic NDE of multilayered structures are analysed.

Lipid body accumulation alters calcium signaling dynamics in immune cells

PubMed Central

Greineisen, William E.; Speck, Mark; Shimoda, Lori M.N.; Sung, Carl; Phan, Nolwenn; Maaetoft-Udsen, Kristina; Stokes, Alexander J.; Turner, Helen

2014-01-01

Summary There is well-established variability in the numbers of lipid bodies (LB) in macrophages, eosinophils, and neutrophils. Similarly to the steatosis observed in adipocytes and hepatocytes during hyperinsulinemia and nutrient overload, immune cell LB hyper-accumulate in response to bacterial and parasitic infection and inflammatory presentations. Recently we described that hyperinsulinemia, both in vitro and in vivo, drives steatosis and phenotypic changes in primary and transformed mast cells and basophils. LB reach high numbers in these steatotic cytosols, and here we propose that they could dramatically impact the transcytoplasmic signaling pathways. We compared calcium release and influx responses at the population and single cell level in normal and steatotic model mast cells. At the population level, all aspects of FcεRI-dependent calcium mobilization, as well as activation of calcium-dependent downstream signalling targets such as NFATC1 phosphorylation are suppressed. At the single cell level, we demonstrate that LB are both sources and sinks of calcium following FcεRI cross-linking. Unbiased analysis of the impact of the presence of LB on the rate of trans-cytoplasmic calcium signals suggest that LB enrichment accelerates calcium propagation, which may reflect a Bernoulli effect. LB abundance thus impacts this fundamental signalling pathway and its downstream targets. PMID:25016314

Non-linear dynamic compensation system

NASA Technical Reports Server (NTRS)

Lin, Yu-Hwan (Inventor); Lurie, Boris J. (Inventor)

1992-01-01

A non-linear dynamic compensation subsystem is added in the feedback loop of a high precision optical mirror positioning control system to smoothly alter the control system response bandwidth from a relatively wide response bandwidth optimized for speed of control system response to a bandwidth sufficiently narrow to reduce position errors resulting from the quantization noise inherent in the inductosyn used to measure mirror position. The non-linear dynamic compensation system includes a limiter for limiting the error signal within preselected limits, a compensator for modifying the limiter output to achieve the reduced bandwidth response, and an adder for combining the modified error signal with the difference between the limited and unlimited error signals. The adder output is applied to control system motor so that the system response is optimized for accuracy when the error signal is within the preselected limits, optimized for speed of response when the error signal is substantially beyond the preselected limits and smoothly varied therebetween as the error signal approaches the preselected limits.

Insulin Signaling in Type 2 Diabetes

PubMed Central

Brännmark, Cecilia; Nyman, Elin; Fagerholm, Siri; Bergenholm, Linnéa; Ekstrand, Eva-Maria; Cedersund, Gunnar; Strålfors, Peter

2013-01-01

Type 2 diabetes originates in an expanding adipose tissue that for unknown reasons becomes insulin resistant. Insulin resistance reflects impairments in insulin signaling, but mechanisms involved are unclear because current research is fragmented. We report a systems level mechanistic understanding of insulin resistance, using systems wide and internally consistent data from human adipocytes. Based on quantitative steady-state and dynamic time course data on signaling intermediaries, normally and in diabetes, we developed a dynamic mathematical model of insulin signaling. The model structure and parameters are identical in the normal and diabetic states of the model, except for three parameters that change in diabetes: (i) reduced concentration of insulin receptor, (ii) reduced concentration of insulin-regulated glucose transporter GLUT4, and (iii) changed feedback from mammalian target of rapamycin in complex with raptor (mTORC1). Modeling reveals that at the core of insulin resistance in human adipocytes is attenuation of a positive feedback from mTORC1 to the insulin receptor substrate-1, which explains reduced sensitivity and signal strength throughout the signaling network. Model simulations with inhibition of mTORC1 are comparable with experimental data on inhibition of mTORC1 using rapamycin in human adipocytes. We demonstrate the potential of the model for identification of drug targets, e.g. increasing the feedback restores insulin signaling, both at the cellular level and, using a multilevel model, at the whole body level. Our findings suggest that insulin resistance in an expanded adipose tissue results from cell growth restriction to prevent cell necrosis. PMID:23400783

Colored Petri net modeling and simulation of signal transduction pathways.

PubMed

Lee, Dong-Yup; Zimmer, Ralf; Lee, Sang Yup; Park, Sunwon

2006-03-01

Presented herein is a methodology for quantitatively analyzing the complex signaling network by resorting to colored Petri nets (CPN). The mathematical as well as Petri net models for two basic reaction types were established, followed by the extension to a large signal transduction system stimulated by epidermal growth factor (EGF) in an application study. The CPN models based on the Petri net representation and the conservation and kinetic equations were used to examine the dynamic behavior of the EGF signaling pathway. The usefulness of Petri nets is demonstrated for the quantitative analysis of the signal transduction pathway. Moreover, the trade-offs between modeling capability and simulation efficiency of this pathway are explored, suggesting that the Petri net model can be invaluable in the initial stage of building a dynamic model.

Dopamine D1 signaling organizes network dynamics underlying working memory.

PubMed

Roffman, Joshua L; Tanner, Alexandra S; Eryilmaz, Hamdi; Rodriguez-Thompson, Anais; Silverstein, Noah J; Ho, New Fei; Nitenson, Adam Z; Chonde, Daniel B; Greve, Douglas N; Abi-Dargham, Anissa; Buckner, Randy L; Manoach, Dara S; Rosen, Bruce R; Hooker, Jacob M; Catana, Ciprian

2016-06-01

Local prefrontal dopamine signaling supports working memory by tuning pyramidal neurons to task-relevant stimuli. Enabled by simultaneous positron emission tomography-magnetic resonance imaging (PET-MRI), we determined whether neuromodulatory effects of dopamine scale to the level of cortical networks and coordinate their interplay during working memory. Among network territories, mean cortical D1 receptor densities differed substantially but were strongly interrelated, suggesting cross-network regulation. Indeed, mean cortical D1 density predicted working memory-emergent decoupling of the frontoparietal and default networks, which respectively manage task-related and internal stimuli. In contrast, striatal D1 predicted opposing effects within these two networks but no between-network effects. These findings specifically link cortical dopamine signaling to network crosstalk that redirects cognitive resources to working memory, echoing neuromodulatory effects of D1 signaling on the level of cortical microcircuits.

Dopamine D1 signaling organizes network dynamics underlying working memory

PubMed Central

Roffman, Joshua L.; Tanner, Alexandra S.; Eryilmaz, Hamdi; Rodriguez-Thompson, Anais; Silverstein, Noah J.; Ho, New Fei; Nitenson, Adam Z.; Chonde, Daniel B.; Greve, Douglas N.; Abi-Dargham, Anissa; Buckner, Randy L.; Manoach, Dara S.; Rosen, Bruce R.; Hooker, Jacob M.; Catana, Ciprian

2016-01-01

Local prefrontal dopamine signaling supports working memory by tuning pyramidal neurons to task-relevant stimuli. Enabled by simultaneous positron emission tomography–magnetic resonance imaging (PET-MRI), we determined whether neuromodulatory effects of dopamine scale to the level of cortical networks and coordinate their interplay during working memory. Among network territories, mean cortical D1 receptor densities differed substantially but were strongly interrelated, suggesting cross-network regulation. Indeed, mean cortical D1 density predicted working memory–emergent decoupling of the frontoparietal and default networks, which respectively manage task-related and internal stimuli. In contrast, striatal D1 predicted opposing effects within these two networks but no between-network effects. These findings specifically link cortical dopamine signaling to network crosstalk that redirects cognitive resources to working memory, echoing neuromodulatory effects of D1 signaling on the level of cortical microcircuits. PMID:27386561

Prediction of SA 349/2 GV blade loads in high speed flight using several rotor analyses

NASA Technical Reports Server (NTRS)

Gaubert, Michel; Yamauchi, Gloria K.

1987-01-01

The influence of blade dynamics, dynamic stall, and transonic aerodynamics on the predictions of rotor loads in high-speed flight are presented. Data were obtained from an Aerospatiale Gazelle SA 349/2 helicopter with three Grande Vitesse blades. Several analyses are used for this investigation. First, blade dynamics effects on the correlation are studied using three rotor analyses which differ mainly in the method of calculating the blade elastic response. Next, an ONERA dynamic stall model is used to predict retreating blade stall. Finally, advancing blade aerodynamic loads are calculated using a NASA-developed rotorcraft analysis coupled with two transonic finite-difference analyses.

Plasmodesmata in integrated cell signalling: insights from development and environmental signals and stresses

PubMed Central

Sager, Ross; Lee, Jung-Youn

2014-01-01

To survive as sedentary organisms built of immobile cells, plants require an effective intercellular communication system, both locally between neighbouring cells within each tissue and systemically across distantly located organs. Such a system enables cells to coordinate their intracellular activities and produce concerted responses to internal and external stimuli. Plasmodesmata, membrane-lined intercellular channels, are essential for direct cell-to-cell communication involving exchange of diffusible factors, including signalling and information molecules. Recent advances corroborate that plasmodesmata are not passive but rather highly dynamic channels, in that their density in the cell walls and gating activities are tightly linked to developmental and physiological processes. Moreover, it is becoming clear that specific hormonal signalling pathways play crucial roles in relaying primary cellular signals to plasmodesmata. In this review, we examine a number of studies in which plasmodesmal structure, occurrence, and/or permeability responses are found to be altered upon given cellular or environmental signals, and discuss common themes illustrating how plasmodesmal regulation is integrated into specific cellular signalling pathways. PMID:25262225

Dynamics of β-adrenergic/cAMP signaling and morphological changes in cultured astrocytes.

PubMed

Vardjan, Nina; Kreft, Marko; Zorec, Robert

2014-04-01

The morphology of astrocytes, likely regulated by cAMP, determines the structural association between astrocytes and the synapse, consequently modulating synaptic function. β-Adrenergic receptors (β-AR), which increase cytosolic cAMP concentration ([cAMP]i ), may affect cell morphology. However, the real-time dynamics of β-AR-mediated cAMP signaling in single live astrocytes and its effect on cell morphology have not been studied. We used the fluorescence resonance energy transfer (FRET)-based cAMP biosensor Epac1-camps to study time-dependent changes in [cAMP]i ; morphological changes in primary rat astrocytes were monitored by real-time confocal microscopy. Stimulation of β-AR by adrenaline, noradrenaline, and isoprenaline, a specific agonist of β-AR, rapidly increased [cAMP]i (∼15 s). The FRET signal response, mediated via β-AR, was faster than in the presence of forskolin (twofold) and dibutyryl-cAMP (>35-fold), which directly activate adenylyl cyclase and Epac1-camps, respectively, likely due to slow entry of these agents into the cytosol. Oscillations in [cAMP]i have not been recorded, indicating that cAMP-dependent processes operate in a slow time domain. Most Epac1-camps expressing astrocytes revealed a morphological change upon β-AR activation and attained a stellate morphology within 1 h. The morphological changes exhibited a bell-shaped dependency on [cAMP]i . The 5-10% decrease in cell cross-sectional area and the 30-50% increase in cell perimeter are likely due to withdrawal of the cytoplasm to the perinuclear region and the appearance of protrusions on the surface of astrocytes. Because astrocyte processes ensheath neurons, β-AR/cAMP-mediated morphological changes can modify the geometry of the extracellular space, affecting synaptic, neuronal, and astrocyte functions in health and disease. Copyright © 2014 Wiley Periodicals, Inc.

Notch signaling dynamics in the adult healthy prostate and in prostatic tumor development.

PubMed

Pedrosa, Ana-Rita; Graça, José L; Carvalho, Sandra; Peleteiro, Maria C; Duarte, António; Trindade, Alexandre

2016-01-01

The Notch signaling pathway has been implicated in prostate development, maintenance and tumorigenesis by its key role in cell-fate determination, differentiation and proliferation. Therefore, we proposed to analyze Notch family members transcription and expression, including ligands (Dll1, 3, 4 and Jagged1 and 2), receptors (Notch1-4) and effectors (Hes1, 2, 5 and Hey1, 2, L), in both normal and tumor bearing mouse prostates to better understand the dynamics of Notch signaling in prostate tumorigenesis. Wild type mice and transgenic adenocarcinoma of the mouse prostate model (TRAMP) mice were sacrificed at 18, 24 or 30 weeks of age and the prostates collected and processed for either whole prostate or prostate cell specific populations mRNA analysis and for protein expression analysis by immunohistochemistry and immunofluorescence. We observed that Dll1 and Dll4 are expressed in the luminal compartment of the mouse healthy prostate, whereas Jagged2 expression is restricted to the basal and stromal compartment. Additionally, Notch2 and Notch4 are normally expressed in the prostate luminal compartment while Notch2 and Notch3 are also expressed in the stromal layer of the healthy prostate. As prostate tumor development takes place, there is up-regulation of Notch components. Particularly, the prostate tumor lesions have increased expression of Jagged1 and 2, of Notch3 and of Hey1. We have also detected the presence of activated Notch3 in prostatic tumors that co-express Jagged1 and ultimately the Hey1 effector. Taken together our results point out the Notch axis Jagged1-2/Notch3/Hey1 to be important for prostate tumor development and worthy of additional functional studies and validation in human clinical disease. © 2015 Wiley Periodicals, Inc.

Ultrasensitive response motifs: basic amplifiers in molecular signalling networks

PubMed Central

Zhang, Qiang; Bhattacharya, Sudin; Andersen, Melvin E.

2013-01-01

Multi-component signal transduction pathways and gene regulatory circuits underpin integrated cellular responses to perturbations. A recurring set of network motifs serve as the basic building blocks of these molecular signalling networks. This review focuses on ultrasensitive response motifs (URMs) that amplify small percentage changes in the input signal into larger percentage changes in the output response. URMs generally possess a sigmoid input–output relationship that is steeper than the Michaelis–Menten type of response and is often approximated by the Hill function. Six types of URMs can be commonly found in intracellular molecular networks and each has a distinct kinetic mechanism for signal amplification. These URMs are: (i) positive cooperative binding, (ii) homo-multimerization, (iii) multistep signalling, (iv) molecular titration, (v) zero-order covalent modification cycle and (vi) positive feedback. Multiple URMs can be combined to generate highly switch-like responses. Serving as basic signal amplifiers, these URMs are essential for molecular circuits to produce complex nonlinear dynamics, including multistability, robust adaptation and oscillation. These dynamic properties are in turn responsible for higher-level cellular behaviours, such as cell fate determination, homeostasis and biological rhythm. PMID:23615029

Brain Signal Variability is Parametrically Modifiable

PubMed Central

Garrett, Douglas D.; McIntosh, Anthony R.; Grady, Cheryl L.

2014-01-01

Moment-to-moment brain signal variability is a ubiquitous neural characteristic, yet remains poorly understood. Evidence indicates that heightened signal variability can index and aid efficient neural function, but it is not known whether signal variability responds to precise levels of environmental demand, or instead whether variability is relatively static. Using multivariate modeling of functional magnetic resonance imaging-based parametric face processing data, we show here that within-person signal variability level responds to incremental adjustments in task difficulty, in a manner entirely distinct from results produced by examining mean brain signals. Using mixed modeling, we also linked parametric modulations in signal variability with modulations in task performance. We found that difficulty-related reductions in signal variability predicted reduced accuracy and longer reaction times within-person; mean signal changes were not predictive. We further probed the various differences between signal variance and signal means by examining all voxels, subjects, and conditions; this analysis of over 2 million data points failed to reveal any notable relations between voxel variances and means. Our results suggest that brain signal variability provides a systematic task-driven signal of interest from which we can understand the dynamic function of the human brain, and in a way that mean signals cannot capture. PMID:23749875

Detection, Evaluation, and Optimization of Optical Signals Generated by Fiber Optic Bragg Gratings Under Dynamic Excitations

NASA Technical Reports Server (NTRS)

Adamovsky, Grigory; Lekki, John; Lock, James A.

2002-01-01

The dynamic response of a fiber optic Bragg grating to mechanical vibrations is examined both theoretically and experimentally. The theoretical expressions describing the consequences of changes in the grating's reflection spectrum are derived for partially coherent beams in an interferometer. The analysis is given in terms of the dominant wavelength, optical bandwidth, and optical path difference of the interfering signals. Changes in the reflection spectrum caused by a periodic stretching and compression of the grating were experimentally measured using an unbalanced Michelson interferometer, a Michelson interferometer with a non-zero optical path difference. The interferometer's sensitivity to changes in dominant wavelength of the interfering beams was measured as a function of interferometer unbalance and was compared to theoretical predictions. The theoretical analysis enables the user to determine the optimum performance for an unbalanced interferometer.

Signal detection via residence-time asymmetry in noisy bistable devices.

PubMed

Bulsara, A R; Seberino, C; Gammaitoni, L; Karlsson, M F; Lundqvist, B; Robinson, J W C

2003-01-01

We introduce a dynamical readout description for a wide class of nonlinear dynamic sensors operating in a noisy environment. The presence of weak unknown signals is assessed via the monitoring of the residence time in the metastable attractors of the system, in the presence of a known, usually time-periodic, bias signal. This operational scenario can mitigate the effects of sensor noise, providing a greatly simplified readout scheme, as well as significantly reduced processing procedures. Such devices can also show a wide variety of interesting dynamical features. This scheme for quantifying the response of a nonlinear dynamic device has been implemented in experiments involving a simple laboratory version of a fluxgate magnetometer. We present the results of the experiments and demonstrate that they match the theoretical predictions reasonably well.

Genome-wide genetic analyses highlight mitogen-activated protein kinase (MAPK) signaling in the pathogenesis of endometriosis.